This repository contains a collection of resources and papers on Diffusion Models.
- Resources
- Papers
A Path to the Variational Diffusion Loss
Alex Alemi
[Website] [Colab]
15 Sep 2022
The Annotated Diffusion Model
Niels Rogge, Kashif Rasul
[Website]
06 Jun 2022
The recent rise of diffusion-based models
Maciej Domagała
[Website]
06 Jun 2022
Introduction to Diffusion Models for Machine Learning
Ryan O'Connor
[Website]
12 May 2022
Improving Diffusion Models as an Alternative To GANs
Arash Vahdat and Karsten Kreis
[Website-Part 1] [Website-Part 2]
26 Apr 2022
An introduction to Diffusion Probabilistic Models
Ayan Das
[Website]
04 Dec 2021
Introduction to deep generative modeling: Diffusion-based Deep Generative Models
Jakub Tomczak
[Website]
30 Aug 2021
What are Diffusion Models?
Lilian Weng
[Website]
11 Jul 2021
Diffusion Models as a kind of VAE
Angus Turner
[Website]
29 June 2021
Generative Modeling by Estimating Gradients of the Data Distribution
Yang Song
[Website]
5 May 2021
Understanding Diffusion Models: A Unified Perspective
Calvin Luo
arXiv 2022. [Paper]
25 Aug 2022
How to Train Your Energy-Based Models
Yang Song, Diederik P. Kingma
arXiv 2022. [Paper]
9 Jan 2021
Diffusion Models | Paper Explanation | Math Explained
Outlier
[Video]
Jun 6 2022
What are Diffusion Models?
Ari Seff
[Video]
20 Apr 2022
Diffusion models explained
AI Coffee Break with Letitia
[Video]
23 Mar 2022
Denoising Diffusion-based Generative Modeling: Foundations and Applications
Karsten Kreis, Ruiqi Gao, Arash Vahdat
[Page]
19 June 2022
Diffusion Probabilistic Models
Jascha Sohl-Dickstein, MIT 6.S192 - Lecture 22
[Video]
19 April 2022
Diffusion Models in Vision: A Survey
Florinel-Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu, Mubarak Shah
arXiv 2022. [Paper]
10 Sep 2022
A Survey on Generative Diffusion Model
Hanqun Cao, Cheng Tan, Zhangyang Gao, Guangyong Chen, Pheng-Ann Heng, Stan Z. Li
arXiv 2022. [Paper]
6 Sep 2022
Diffusion Models: A Comprehensive Survey of Methods and Applications
Ling Yang1, Zhilong Zhang1, Shenda Hong, Wentao Zhang
arXiv 2022. [Paper]
2 Sep 2022
On Distillation of Guided Diffusion Models
Chenlin Meng, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans
arXiv 2022. [Paper]
6 Oct 2022
Improving Sample Quality of Diffusion Model Using Self-Attention Guidance
Susung Hong, Gyuseong Lee, Wooseok Jang, Seungryong Kim
arXiv 2022. [Paper] [Project]
3 Oct 2022
OCD: Learning to Overfit with Conditional Diffusion Models
Shahar Shlomo Lutati, Lior Wolf
arXiv 2022. [Paper] [Github]
2 Oct 2022
Generated Faces in the Wild: Quantitative Comparison of Stable Diffusion, Midjourney and DALL-E 2
Ali Borji
arXiv 2022. [Paper] [Github]
2 Oct 2022
Denoising MCMC for Accelerating Diffusion-Based Generative Models
Beomsu Kim, Jong Chul Ye
arXiv 2022. [Paper] [Github]
29 Sep 2022
All are Worth Words: a ViT Backbone for Score-based Diffusion Models
Fan Bao, Chongxuan Li, Yue Cao, Jun Zhu
arXiv 2022. [Paper]
25 Sep 2022
Neural Wavelet-domain Diffusion for 3D Shape Generation
Ka-Hei Hui, Ruihui Li, Jingyu Hu, Chi-Wing Fu
arXiv 2022. [Paper]
19 Sep 2022
Can segmentation models be trained with fully synthetically generated data?
Virginia Fernandez, Walter Hugo Lopez Pinaya, Pedro Borges, Petru-Daniel Tudosiu, Mark S Graham, Tom Vercauteren, M Jorge Cardoso
arXiv 2022. [Paper]
17 Sep 2022
Blurring Diffusion Models
Emiel Hoogeboom, Tim Salimans
arXiv 2022. [Paper]
12 Sep 2022
Soft Diffusion: Score Matching for General Corruptions
Giannis Daras, Mauricio Delbracio, Hossein Talebi, Alexandros G. Dimakis, Peyman Milanfar
arXiv 2022. [Paper]
12 Sep 2022
Improved Masked Image Generation with Token-Critic
José Lezama, Huiwen Chang, Lu Jiang, Irfan Essa
arXiv 2022. [Paper]
9 Sep 2022
Let us Build Bridges: Understanding and Extending Diffusion Generative Models
Xingchao Liu, Lemeng Wu, Mao Ye, Qiang Liu
arXiv 2022. [Paper]
31 Aug 2022
Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis
Wan-Cyuan Fan, Yen-Chun Chen, DongDong Chen, Yu Cheng, Lu Yuan, Yu-Chiang Frank Wang
arXiv 2022. [Paper]
29 Aug 2022
Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise
Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie S. Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein
arXiv 2022. [Paper] [Github]
19 Aug 2022
Enhancing Diffusion-Based Image Synthesis with Robust Classifier Guidance
Bahjat Kawar, Roy Ganz, Michael Elad
arXiv 2022. [Paper]
18 Aug 2022
Your ViT is Secretly a Hybrid Discriminative-Generative Diffusion Model
Xiulong Yang1, Sheng-Min Shih1, Yinlin Fu, Xiaoting Zhao, Shihao Ji
arXiv 2022. [Paper] [Github]
16 Aug 2022
Applying Regularized Schrödinger-Bridge-Based Stochastic Process in Generative Modeling
Ki-Ung Song
arXiv 2022. [Paper] [Github]
15 Aug 2022
Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning
Ting Chen, Ruixiang Zhang, Geoffrey Hinton
arXiv 2022. [Paper]
8 Aug 2022
Pyramidal Denoising Diffusion Probabilistic Models
Dohoon Ryu, Jong Chul Ye
arXiv 2022. [Paper]
3 Aug 2022
Progressive Deblurring of Diffusion Models for Coarse-to-Fine Image Synthesis
Sangyun Lee, Hyungjin Chung, Jaehyeon Kim, Jong Chul Ye
arxiv 2022. [Paper] [Github]
16 Jul 2022
Improving Diffusion Model Efficiency Through Patching
Troy Luhman, Eric Luhman
arXiv 2022. [Paper] [Github]
9 Jul 2022
Accelerating Score-based Generative Models with Preconditioned Diffusion Sampling
Hengyuan Ma, Li Zhang, Xiatian Zhu, Jianfeng Feng
arXiv 2022. [Paper]
5 Jul 2022
SPI-GAN: Distilling Score-based Generative Models with Straight-Path Interpolations
Jinsung Jeon, Noseong Park
arxiv 2022. [Paper]
29 Jun 2022
Entropy-driven Sampling and Training Scheme for Conditional Diffusion Generation
Shengming Li, Guangcong Zheng, Hui Wang, Taiping Yao, Yang Chen, Shoudong Ding, Xi Li
arXiv 2022. [Paper]
23 Jun 2022
Generative Modelling With Inverse Heat Dissipation
Severi Rissanen, Markus Heinonen, Arno Solin
arXiv 2022. [Paper] [Project]
21 Jun 2022
Diffusion models as plug-and-play priors
Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras
NeurIPS 2022. [Paper] [Github]
17 June 2022
A Flexible Diffusion Model
Weitao Du, Tao Yang, He Zhang, Yuanqi Du
arXiv 2022. [Paper]
17 Jun 2022
Lossy Compression with Gaussian Diffusion
Lucas Theis, Tim Salimans, Matthew D. Hoffman, Fabian Mentzer
arXiv 2022. [Paper]
17 Jun 2022
Maximum Likelihood Training for Score-Based Diffusion ODEs by High-Order Denoising Score Matching
Cheng Lu, Kaiwen Zheng, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
ICML 2022. [Paper] [Github]
16 Jun 2022
Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models
Fan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu, Bo Zhang
ICML 2022. [Paper] [Github]
15 Jun 2022
Discrete Contrastive Diffusion for Cross-Modal and Conditional Generation
Ye Zhu, Yu Wu, Kyle Olszewski, Jian Ren, Sergey Tulyakov, Yan Yan
arXiv 2022. [Paper] [Github]
15 Jun 2022
gDDIM: Generalized denoising diffusion implicit models
Qinsheng Zhang, Molei Tao, Yongxin Chen
arXiv 2022. [Paper] [Github]
11 Jun 2022
How Much is Enough? A Study on Diffusion Times in Score-based Generative Models
Giulio Franzese, Simone Rossi, Lixuan Yang, Alessandro Finamore, Dario Rossi, Maurizio Filippone, Pietro Michiardi
arXiv 2022. [Paper]
10 Jun 2022
Image Generation with Multimodal Priors using Denoising Diffusion Probabilistic Models
Nithin Gopalakrishnan Nair, Wele Gedara Chaminda Bandara, Vishal M Patel
arXiv 2022. [Paper]
10 Jun 2022
Accelerating Score-based Generative Models for High-Resolution Image Synthesis
Hengyuan Ma, Li Zhang, Xiatian Zhu, Jingfeng Zhang, Jianfeng Feng
arXiv 2022. [Paper]
8 Jun 2022
Diffusion-GAN: Training GANs with Diffusion
Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou
arXiv 2022. [Paper]
5 Jun 2022
DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
NeurrIPS 2022. [Paper] [Github]
2 Jun 2022
Elucidating the Design Space of Diffusion-Based Generative Models
Tero Karras, Miika Aittala, Timo Aila, Samuli Laine
NeurIPS 2022. [Paper]
1 Jun 2022
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models
Kamil Deja, Anna Kuzina, Tomasz Trzciński, Jakub M. Tomczak
NeurIPS 2022. [Paper]
31 May 2022
Few-Shot Diffusion Models
Giorgio Giannone, Didrik Nielsen, Ole Winther
arXiv 2022. [Paper]
30 May 2022
A Continuous Time Framework for Discrete Denoising Models
Andrew Campbell, Joe Benton, Valentin De Bortoli, Tom Rainforth, George Deligiannidis, Arnaud Doucet
arXiv 2022. [Paper]
30 May 2022
Maximum Likelihood Training of Implicit Nonlinear Diffusion Models
Dongjun Kim, Byeonghu Na, Se Jung Kwon, Dongsoo Lee, Wanmo Kang, Il-Chul Moon
NeurIPS 2022. [Paper]
27 May 2022
Accelerating Diffusion Models via Early Stop of the Diffusion Process
Zhaoyang Lyu, Xudong XU, Ceyuan Yang, Dahua Lin, Bo Dai
ICML 2022. [Paper]
25 May 2022
On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models
Vedant Singh1, Surgan Jandial1, Ayush Chopra, Siddharth Ramesh, Balaji Krishnamurthy, Vineeth N. Balasubramanian
arxiv 2022. [Paper]
8 May 2022
Subspace Diffusion Generative Models
Bowen Jing, Gabriele Corso, Renato Berlinghieri, Tommi Jaakkola
arXiv 2022. [Paper] [Github]
3 May 2022
Fast Sampling of Diffusion Models with Exponential Integrator
Qinsheng Zhang, Yongxin Chen
arXiv 2022. [Paper]
29 Apr 2022
Retrieval-Augmented Diffusion Models
Andreas Blattmann1, Robin Rombach1, Kaan Oktay, Björn Ommer
arXiv 2022. [Paper]
25 Apr 2022
Perception Prioritized Training of Diffusion Models
Jooyoung Choi, Jungbeom Lee, Chaehun Shin, Sungwon Kim, Hyunwoo Kim, Sungroh Yoon
arXiv 2022. [Paper] [Github]
1 Apr 2022
Generating High Fidelity Data from Low-density Regions using Diffusion Models
Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton Ferrer
arXiv 2022. [Paper]
31 Mar 2022
Diffusion Models for Counterfactual Explanations
Guillaume Jeanneret, Loïc Simon, Frédéric Jurie
arXiv 2022. [Paper]
29 Mar 2022
Denoising Likelihood Score Matching for Conditional Score-based Data Generation
Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, Yi-Chen Lo, Chia-Che Chang, Yu-Lun Liu, Yu-Lin Chang, Chia-Ping Chen, Chun-Yi Lee
ICLR 2022. [Paper]
27 Mar 2022
Dynamic Dual-Output Diffusion Models
Yaniv Benny, Lior Wolf
arXiv 2022. [Paper]
8 Mar 2022
Conditional Simulation Using Diffusion Schrödinger Bridges
Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
arXiv 2022. [Paper]
27 Feb 2022
Diffusion Causal Models for Counterfactual Estimation
Pedro Sanchez, Sotirios A. Tsaftaris
PMLR 2022. [Paper]
21 Feb 2022
Pseudo Numerical Methods for Diffusion Models on Manifolds
Luping Liu, Yi Ren, Zhijie Lin, Zhou Zhao
ICLR 2022. [Paper] [Github]
20 Feb 2022
Truncated Diffusion Probabilistic Models
Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou
arXiv 2022. [Paper]
19 Feb 2022
Understanding DDPM Latent Codes Through Optimal Transport
Valentin Khrulkov, Ivan Oseledets
arXiv 2022. [Paper]
14 Feb 2022
Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality
Daniel Watson, William Chan, Jonathan Ho, Mohammad Norouzi
ICLR 2022. [Paper]
11 Feb 2022
Progressive Distillation for Fast Sampling of Diffusion Models
Tim Salimans, Jonathan Ho
ICLR 2022. [Paper]
1 Feb 2022
Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models
Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang
arXiv 2022. [Paper]
17 Jan 2022
DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents
Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar
arXiv 2022. [Paper] [Github]
2 Jan 2022
Itô-Taylor Sampling Scheme for Denoising Diffusion Probabilistic Models using Ideal Derivatives
Hideyuki Tachibana, Mocho Go, Muneyoshi Inahara, Yotaro Katayama, Yotaro Watanabe
arXiv 2021. [Paper]
26 Dec 2021
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
Alex Nichol1, Prafulla Dhariwal1, Aditya Ramesh1, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, Mark Chen
ICML 2021. [Paper] [Github]
20 Dec 2021
High-Resolution Image Synthesis with Latent Diffusion Models
Robin Rombach1, Andreas Blattmann1, Dominik Lorenz, Patrick Esser, Björn Ommer
arXiv 2021. [Paper] [Github]
20 Dec 2021
Heavy-tailed denoising score matching
Jacob Deasy, Nikola Simidjievski, Pietro Liò
arXiv 2021. [Paper]
17 Dec 2021
High Fidelity Visualization of What Your Self-Supervised Representation Knows About
Florian Bordes, Randall Balestriero, Pascal Vincent
arXiv 2021. [Paper]
16 Dec 2021
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
Zhisheng Xiao, Karsten Kreis, Arash Vahdat
arXiv 2021. [Paper] [Project]
15 Dec 2021
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion
Tim Dockhorn, Arash Vahdat, Karsten Kreis
arXiv 2021. [Paper] [Project]
14 Dec 2021
More Control for Free! Image Synthesis with Semantic Diffusion Guidance
Xihui Liu, Dong Huk Park, Samaneh Azadi, Gong Zhang, Arman Chopikyan, Yuxiao Hu, Humphrey Shi, Anna Rohrbach, Trevor Darrell
arXiv 2021. [Paper]
10 Dec 2021
Global Context with Discrete Diffusion in Vector Quantised Modelling for Image Generation
Minghui Hu, Yujie Wang, Tat-Jen Cham, Jianfei Yang, P.N.Suganthan
arXiv 2021. [Paper]
3 Dec 2021
Diffusion Autoencoders: Toward a Meaningful and Decodable Representation
Konpat Preechakul, Nattanat Chatthee, Suttisak Wizadwongsa, Supasorn Suwajanakorn
CVPR 2022. [Paper] [Project] [Github]
30 Dec 2021
Conditional Image Generation with Score-Based Diffusion Models
Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann
arXiv 2021. [Paper]
26 Nov 2021
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes
Sam Bond-Taylor1, Peter Hessey1, Hiroshi Sasaki, Toby P. Breckon, Chris G. Willcocks
arXiv 2021. [Paper] [Github]
24 Nov 2021
Diffusion Normalizing Flow
Qinsheng Zhang, Yongxin Chen
NeurIPS 2021. [Paper] [Github]
14 Oct 2021
Denoising Diffusion Gamma Models
Eliya Nachmani1, Robin San Roman1, Lior Wolf
arXiv 2021. [Paper]
10 Oct 2021
Score-based Generative Neural Networks for Large-Scale Optimal Transport
Max Daniels, Tyler Maunu, Paul Hand
arXiv 2021. [Paper]
7 Oct 2021
Score-Based Generative Classifiers
Roland S. Zimmermann, Lukas Schott, Yang Song, Benjamin A. Dunn, David A. Klindt
arXiv 2021. [Paper]
1 Oct 2021
Classifier-Free Diffusion Guidance
Jonathan Ho, Tim Salimans
NeurIPS Workshop 2021. [Paper]
28 Sep 2021
Bilateral Denoising Diffusion Models
Max W. Y. Lam, Jun Wang, Rongjie Huang, Dan Su, Dong Yu
arXiv 2021. [Paper] [Project]
26 Aug 2021
ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis
Patrick Esser1, Robin Rombach1, Andreas Blattmann1, Björn Ommer
NeurIPS 2021. [Paper] [Project]
19 Aug 2021
ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models
Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, Sungroh Yoon
ICCV 2021 (Oral). [Paper] [Github]
6 Aug 2021
SDEdit: Image Synthesis and Editing with Stochastic Differential Equations
Chenlin Meng, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, Stefano Ermon
arXiv 2021. [Paper] [Project] [Github]
2 Aug 2021
Structured Denoising Diffusion Models in Discrete State-Spaces
Jacob Austin1, Daniel D. Johnson1, Jonathan Ho, Daniel Tarlow, Rianne van den Berg
NeurIPS 2021. [Paper]
7 Jul 2021
Variational Diffusion Models
Diederik P. Kingma1, Tim Salimans1, Ben Poole, Jonathan Ho
arXiv 2021. [Paper] [Github]
1 Jul 2021
Diffusion Priors In Variational Autoencoders
Antoine Wehenkel1, Gilles Louppe1
ICML Workshop 2021. [Paper]
29 Jun 2021
Deep Generative Learning via Schrödinger Bridge
Gefei Wang, Yuling Jiao, Qian Xu, Yang Wang, Can Yang
ICML 2021. [Paper]
19 Jun 2021
Non Gaussian Denoising Diffusion Models
Eliya Nachmani1, Robin San Roman1, Lior Wolf
arXiv 2021. [Paper] [Project]
14 Jun 2021
D2C: Diffusion-Denoising Models for Few-shot Conditional Generation
Abhishek Sinha1, Jiaming Song1, Chenlin Meng, Stefano Ermon
arXiv 2021. [Paper] [Project] [Github]
12 Jun 2021
Score-based Generative Modeling in Latent Space
Arash Vahdat1, Karsten Kreis1, Jan Kautz
arXiv 2021. [Paper]
10 Jun 2021
Learning to Efficiently Sample from Diffusion Probabilistic Models
Daniel Watson, Jonathan Ho, Mohammad Norouzi, William Chan
arXiv 2021. [Paper]
7 Jun 2021
A Variational Perspective on Diffusion-Based Generative Models and Score Matching
Chin-Wei Huang, Jae Hyun Lim, Aaron Courville
NeurIPS 2021. [Paper] [Github]
5 Jun 2021
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling
Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet
arXiv 2021. [Paper] [Project] [Github]
1 Jun 2021
On Fast Sampling of Diffusion Probabilistic Models
Zhifeng Kong, Wei Ping
ICML Workshop 2021. [Paper] [Github]
31 May 2021
Cascaded Diffusion Models for High Fidelity Image Generation
Jonathan Ho1, Chitwan Saharia1, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans
arXiv 2021. [Paper] [Project]
30 May 2021
Gotta Go Fast When Generating Data with Score-Based Models
Alexia Jolicoeur-Martineau, Ke Li, Rémi Piché-Taillefer, Tal Kachman, Ioannis Mitliagkas
arXiv 2021. [Paper] [Github]
28 May 2021
Diffusion Models Beat GANs on Image Synthesis
Prafulla Dhariwal1, Alex Nichol1
arXiv 2021. [Paper] [Github]
11 May 2021
Image Super-Resolution via Iterative Refinement
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi
arXiv 2021. [Paper] [Project] [Github]
15 Apr 2021
Noise Estimation for Generative Diffusion Models
Robin San-Roman1, Eliya Nachmani1, Lior Wolf
arXiv 2021. [Paper]
6 Apr 2021
Improved Denoising Diffusion Probabilistic Models
Alex Nichol1, Prafulla Dhariwal1
ICLR 2021. [Paper] [Github]
18 Feb 2021
Maximum Likelihood Training of Score-Based Diffusion Models
Yang Song1, Conor Durkan1, Iain Murray, Stefano Ermon
arXiv 2021. [Paper]
22 Jan 2021
Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed
Eric Luhman1, Troy Luhman1
arXiv 2021. [Paper] [Github]
7 Jan 2021
Learning Energy-Based Models by Diffusion Recovery Likelihood
Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma
ICLR 2021. [Paper] [Github]
15 Dec 2020
Score-Based Generative Modeling through Stochastic Differential Equations
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole
ICLR 2021 (Oral). [Paper] [Github]
26 Nov 2020
Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models
Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang
ICML 2021. [Paper]
16 Oct 2020
Denoising Diffusion Implicit Models
Jiaming Song, Chenlin Meng, Stefano Ermon
ICLR 2021. [Paper] [Github]
6 Oct 2020
Adversarial score matching and improved sampling for image generation
Alexia Jolicoeur-Martineau1, Rémi Piché-Taillefer1, Rémi Tachet des Combes, Ioannis Mitliagkas
ICLR 2021. [Paper] [Github]
11 Sep 2020
Denoising Diffusion Probabilistic Models
Jonathan Ho, Ajay Jain, Pieter Abbeel
NeurIPS 2020. [Paper] [Github] [Github2]
19 Jun 2020
Improved Techniques for Training Score-Based Generative Models
Yang Song, Stefano Ermon
NeurIPS 2020. [Paper] [Github]
16 Jun 2020
Generative Modeling by Estimating Gradients of the Data Distribution
Yang Song, Stefano Ermon
NeurIPS 2019. [Paper] [Project] [Github]
12 Jul 2019
Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit
Belinda Tzen, Maxim Raginsky
arXiv 2019. [Paper]
23 May 2019
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, Surya Ganguli
ICML 2015. [Paper] [Github]
2 Mar 2015
Anatomically constrained CT image translation for heterogeneous blood vessel segmentation
Giammarco La Barbera, Haithem Boussaid, Francesco Maso, Sabine Sarnacki, Laurence Rouet, Pietro Gori, Isabelle Bloch
BMVC 2022. [Paper]
4 Oct 2022
Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentation
Boah Kim1, Yujin Oh1, Jong Chul Ye
arXiv 2022. [Paper]
29 Sep 2022
Can segmentation models be trained with fully synthetically generated data?
Virginia Fernandez, Walter Hugo Lopez Pinaya, Pedro Borges, Petru-Daniel Tudosiu, Mark S Graham, Tom Vercauteren, M Jorge Cardoso
arXiv 2022. [Paper]
17 Sep 2022
Let us Build Bridges: Understanding and Extending Diffusion Generative Models
Xingchao Liu, Lemeng Wu, Mao Ye, Qiang Liu
arXiv 2022. [Paper]
31 Aug 2022
Semantic Image Synthesis via Diffusion Models
Weilun Wang, Jianmin Bao, Wengang Zhou, Dongdong Chen, Dong Chen, Lu Yuan, Houqiang Li
arXiv 2022. [Paper]
30 Jun 2022
Remote Sensing Change Detection (Segmentation) using Denoising Diffusion Probabilistic Models
Wele Gedara Chaminda Bandara, Nithin Gopalakrishnan Nair, Vishal M. Patel
arXiv 2022. [Paper] [Github]
23 Jun 2022
Diffusion models as plug-and-play priors
Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras
arXiv 2022. [Paper]
17 Jun 2022
Decoder Denoising Pretraining for Semantic Segmentation
Emmanuel Brempong Asiedu, Simon Kornblith, Ting Chen, Niki Parmar, Matthias Minderer, Mohammad Norouzi
arXiv 2022. [Paper]
23 May 2022
Diffusion Models for Implicit Image Segmentation Ensembles
Julia Wolleb1, Robin Sandkühler1, Florentin Bieder, Philippe Valmaggia, Philippe C. Cattin
MIDL 2021. [Paper]
6 Dec 2021
Label-Efficient Semantic Segmentation with Diffusion Models
Dmitry Baranchuk, Ivan Rubachev, Andrey Voynov, Valentin Khrulkov, Artem Babenko
ICLR 2021. [Paper] [Github]
6 Dec 2021
SegDiff: Image Segmentation with Diffusion Probabilistic Models
Tomer Amit, Eliya Nachmani, Tal Shaharbany, Lior Wolf
arXiv 2021. [Paper]
1 Dec 2021
Anatomically constrained CT image translation for heterogeneous blood vessel segmentation
Giammarco La Barbera, Haithem Boussaid, Francesco Maso, Sabine Sarnacki, Laurence Rouet, Pietro Gori, Isabelle Bloch
BMVC 2022. [Paper]
4 Oct 2022
Diffusion-based Image Translation using Disentangled Style and Content Representation
Gihyun Kwon, Jong Chul Ye
arXiv 2022. [Paper]
30 Sep 2022
MIDMs: Matching Interleaved Diffusion Models for Exemplar-based Image Translation
Junyoung Seo1, Gyuseong Lee1, Seokju Cho, Jiyoung Lee, Seungryong Kim
arXiv 2022. [Paper]
22 Sep 2022
T2V-DDPM: Thermal to Visible Face Translation using Denoising Diffusion Probabilistic Models
Nithin Gopalakrishnan Nair, Vishal M. Patel
arXiv 2022. [Paper]
19 Sep 2022
Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models
Ozan Özdenizci, Robert Legenstein
arXiv 2022. [Paper]
29 Jul 2022
Non-Uniform Diffusion Models
Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann
arXiv 2022. [Paper]
20 Jul 2022
Unsupervised Medical Image Translation with Adversarial Diffusion Models
Muzaffer Özbey, Salman UH Dar, Hasan A Bedel, Onat Dalmaz, Şaban Özturk, Alper Güngör, Tolga Çukur
arXiv 2022. [Paper]
17 Jul 2022
EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations
Min Zhao, Fan Bao, Chongxuan Li, Jun Zhu
arXiv 2022. [Paper]
14 Jul 2022
Discrete Contrastive Diffusion for Cross-Modal and Conditional Generation
Ye Zhu, Yu Wu, Kyle Olszewski, Jian Ren, Sergey Tulyakov, Yan Yan
arXiv 2022. [Paper] [Github]
15 Jun 2022
SAR Despeckling using a Denoising Diffusion Probabilistic Model
Malsha V. Perera, Nithin Gopalakrishnan Nair, Wele Gedara Chaminda Bandara, Vishal M. Patel
arXiv 2022. [Paper]
9 Jun 2022
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25 May 2022
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arXiv 2022. [Paper]
16 May 2022
The Swiss Army Knife for Image-to-Image Translation: Multi-Task Diffusion Models
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arXiv 2022. [Paper]
6 Apr 2022
Dual Diffusion Implicit Bridges for Image-to-Image Translation
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arXiv 2022. [Paper]
16 Mar 2022
Denoising Diffusion Restoration Models
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NeurIPS 2022. [Paper]
27 Jan 2022
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arXiv 2021. [Paper]
9 Dec 2021
Diffusion Autoencoders: Toward a Meaningful and Decodable Representation
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arXiv 2021. [Paper] [Project]
30 Dec 2021
Conditional Image Generation with Score-Based Diffusion Models
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arXiv 2021. [Paper]
26 Nov 2021
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ICCV 2021 (Oral). [Paper] [Github]
6 Aug 2021
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arXiv 2021. [Paper]
12 Apr 2021
Diffusion Posterior Sampling for General Noisy Inverse Problems
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arXiv 2022. [Paper] [Github]
29 Sep 2022
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arXiv 2022. [Paper] [Github]
24 Sep 2022
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arXiv 2022. [Paper] [Github]
19 Aug 2022
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arXiv 2022. [Paper]
20 Jul 2022
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2 Jan 2022
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CVPR 2022. [Paper] [Github]
20 Dec 2021
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CVPR 2022. [Paper]
9 Dec 2021
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CVPR 2022. [Paper]
5 Dec 2021
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arXiv 2021. [Paper]
26 Nov 2021
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NeurIPS 2022. [Paper]
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ICLR 2022. [Paper]
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ICCV 2021 (Oral). [Paper] [Github]
6 Aug 2021
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15 Apr 2021
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17 Sep 2022
Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise
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19 Aug 2022
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arXiv 2022. [Paper]
20 Jul 2022
Improving Diffusion Models for Inverse Problems using Manifold Constraints
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arXiv 2022. [Paper]
2 Jun 2022
Denoising Diffusion Restoration Models
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ICLR 2022 Workshop (Oral). [Paper]
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24 Jan 2022
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20 Dec 2021
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CVPR 2022. [Paper]
9 Dec 2021
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26 Nov 2021
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes
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24 Nov 2021
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26 Aug 2022
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Omri Avrahami, Ohad Fried, Dani Lischinski
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6 Jun 2022
High-Resolution Image Synthesis with Latent Diffusion Models
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20 Dec 2021
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15 Dec 2021
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6 Aug 2021
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2 Aug 2021
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5 Oct 2022
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5 Oct 2022
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3 Oct 2022
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29 Sep 2022
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29 Sep 2022
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arXiv 2022. [Paper]
29 Sep 2022
Draw Your Art Dream: Diverse Digital Art Synthesis with Multimodal Guided Diffusion
Nisha Huang, Fan Tang, Weiming Dong, Changsheng Xu
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27 Sep 2022
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25 Sep 2022
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23 Sep 2022
The Biased Artist: Exploiting Cultural Biases via Homoglyphs in Text-Guided Image Generation Models
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19 Sep 2022
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14 Sep 2022
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26 Jul 2022
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15 Jun 2022
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3 Jun 2022
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1 Jun 2022
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31 May 2022
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23 May 2022
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25 Apr 2022
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13 Apr 2022
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arXiv 2022. [Paper]
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More Control for Free! Image Synthesis with Semantic Diffusion Guidance
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10 Dec 2021
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29 Nov 2021
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29 Nov 2021
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CVPR 2022. [Paper]
6 Oct 2021
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BMVC 2022. [Paper]
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arXiv 2022. [Paper]
29 Sep 2022
Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentation
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arXiv 2022. [Paper]
29 Sep 2022
Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models
Qing Lyu, Ge Wang
arXiv 2022. [Paper]
24 Sep 2022
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arXiv 2022. [Paper]
15 Sep 2022
PET image denoising based on denoising diffusion probabilistic models
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arXiv 2022. [Paper]
13 Sep 2022
Self-Score: Self-Supervised Learning on Score-Based Models for MRI Reconstruction
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IEEE TMI 2022. [Paper]
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arXiv 2022. [Paper]
10 Aug 2022
What is Healthy? Generative Counterfactual Diffusion for Lesion Localization
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25 Jul 2022
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Adaptive Diffusion Priors for Accelerated MRI Reconstruction
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A Novel Unified Conditional Score-based Generative Framework for Multi-modal Medical Image Completion
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7 Jul 2022
Cross-Modal Transformer GAN: A Brain Structure-Function Deep Fusing Framework for Alzheimer's Disease
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arXiv 2022. [Paper]
20 Jun 2022
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arXiv 2022. [Paper] [Github]
27 Jun 2022
Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models
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arXiv 2022. [Paper]
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arXiv 2022. [Paper]
2 Jun 2022
AnoDDPM: Anomaly Detection with Denoising Diffusion Probabilistic Models using Simplex Noise
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6 Apr 2022
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arXiv 2022. [Paper]
23 Mar 2022
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arXiv 2022. [Paper] [Github]
8 Mar 2022
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8 Mar 2022
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5 Mar 2022
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3 Feb 2022
Unsupervised Denoising of Retinal OCT with Diffusion Probabilistic Model
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27 Jan 2022
Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction
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9 Dec 2021
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15 Nov 2021
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MIA 2021. [Paper] [Github]
8 Oct 2021
Imagen Video: High Definition Video Generation with Diffusion Models
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arXiv 2022. [Paper]
5 Oct 2022
Make-A-Video: Text-to-Video Generation without Text-Video Data
Uriel Singer, Adam Polyak, Thomas Hayes, Xi Yin, Jie An, Songyang Zhang, Qiyuan Hu, Harry Yang, Oron Ashual, Oran Gafni, Devi Parikh, Sonal Gupta, Yaniv Taigman
arXiv 2022. [Paper]
29 Sep 2022
Diffusion Models for Video Prediction and Infilling
Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi
arXiv 2022. [Paper]
15 Jun 2022
Flexible Diffusion Modeling of Long Videos
William Harvey, Saeid Naderiparizi, Vaden Masrani, Christian Weilbach, Frank Wood
arXiv 2022. [Paper] [Github]
23 May 2022
MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation
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19 May 2022
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NeurIPS 2022. [Paper]
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Ruihan Yang, Prakhar Srivastava, Stephan Mandt
arXiv 2022. [Paper] [Github]
16 Mar 2022
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Mao Ye, Lemeng Wu, Qiang Liu
NeruIPS 2022. [Paper]
2 Sep 2022
Let us Build Bridges: Understanding and Extending Diffusion Generative Models
Xingchao Liu, Lemeng Wu, Mao Ye, Qiang Liu
arXiv 2022. [Paper]
31 Aug 2022
PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition
Jiachen Sun, Weili Nie, Zhiding Yu, Z. Morley Mao, Chaowei Xiao
arXiv 2022. [Paper]
21 Aug 2022
A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion
Zhaoyang Lyu, Zhifeng Kong, Xudong Xu, Liang Pan, Dahua Lin
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7 Dec 2021
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Shitong Luo, Wei Hu
ICCV 2021. [Paper] [Github]
23 Jul 2021
3D Shape Generation and Completion through Point-Voxel Diffusion
Linqi Zhou, Yilun Du, Jiajun Wu
ICCV 2021. [Paper] [Project]
8 Apr 2021
Diffusion Probabilistic Models for 3D Point Cloud Generation
Shitong Luo, Wei Hu
CVPR 2021. [Paper] [Github]
2 Mar 2021
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Yan Zheng, Lemeng Wu, Xingchao Liu, Zhen Chen, Qiang Liu, Qixing Huang
arXiv 2022. [Paper]
6 Oct 2022
Denoising Diffusion Probabilistic Models for Styled Walking Synthesis
Edmund J. C. Findlay, Haozheng Zhang, Ziyi Chang, Hubert P. H. Shum
arXiv 2022. [Paper]
29 Sep 2022
Human Motion Diffusion Model
Guy Tevet, Sigal Raab, Brian Gordon, Yonatan Shafir, Amit H. Bermano, Daniel Cohen-Or
arXiv 2022. [Paper] [Project]
29 Sep 2022
SE(3)-DiffusionFields: Learning cost functions for joint grasp and motion optimization through diffusion
Julen Urain, Niklas Funk, Georgia Chalvatzaki, Jan Peters
arXiv 2022. [Paper] [Github]
8 Sep 2022
FLAME: Free-form Language-based Motion Synthesis & Editing
Jihoon Kim, Jiseob Kim, Sungjoon Choi
arXiv 2022. [Paper]
1 Sep 2022
MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model
Mingyuan Zhang, Zhongang Cai, Liang Pan, Fangzhou Hong, Xinying Guo, Lei Yang, Ziwei Liu
arXiv 2022. [Paper] [Project]
31 Aug 2022
Planning with Diffusion for Flexible Behavior Synthesis
Michael Janner, Yilun Du, Joshua B. Tenenbaum, Sergey Levine
ICML 2022. [Paper] [Github]
20 May 2022
Stochastic Trajectory Prediction via Motion Indeterminacy Diffusion
Tianpei Gu1, Guangyi Chen1, Junlong Li, Chunze Lin, Yongming Rao, Jie Zhou, Jiwen Lu
CVPR 2022. [Paper] [Github]
25 Mar 2022
DiffuStereo: High Quality Human Reconstruction via Diffusion-based Stereo Using Sparse Cameras
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ECCV 2022. [Paper] [Project] [Github]
16 Jul 2022
PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition
Jiachen Sun, Weili Nie, Zhiding Yu, Z. Morley Mao, Chaowei Xiao
arXiv 2022. [Paper]
21 Aug 2022
Threat Model-Agnostic Adversarial Defense using Diffusion Models
Tsachi Blau, Roy Ganz, Bahjat Kawar, Alex Bronstein, Michael Elad
arXiv 2022. [Paper]
17 Jul 2022
Back to the Source: Diffusion-Driven Test-Time Adaptation
Jin Gao1, Jialing Zhang1, Xihui Liu, Trevor Darrell, Evan Shelhamer, Dequan Wang
arXiv 2022. [Paper]
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Guided Diffusion Model for Adversarial Purification from Random Noise
Quanlin Wu, Hang Ye, Yuntian Gu
arXiv 2022. [Paper]
17 Jun 2022
(Certified!!) Adversarial Robustness for Free!
Nicholas Carlini, Florian Tramer, Krishnamurthy (Dj)Dvijotham, J. Zico Kolter
arXiv 2022. [Paper]
21 Jun 2022
Guided Diffusion Model for Adversarial Purification
Jinyi Wang1, Zhaoyang Lyu1, Dahua Lin, Bo Dai, Hongfei Fu
ICML 2022. [Paper] [Github]
30 May 2022
Diffusion Models for Adversarial Purification
Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar
ICML 2022. [Paper] [Project] [Github]
16 May 2022
TFDPM: Attack detection for cyber-physical systems with diffusion probabilistic models
Tijin Yan, Tong Zhou, Yufeng Zhan, Yuanqing Xia
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20 Dec 2021
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Jongmin Yoon, Sung Ju Hwang, Juho Lee
ICML 2021. [Paper] [Github]
11 Jun 2021
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Bahjat Kawar1, Jiaming Song1, Stefano Ermon, Michael Elad
arXiv 2022. [Paper]
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AT-DDPM: Restoring Faces degraded by Atmospheric Turbulence using Denoising Diffusion Probabilistic Models
Nithin Gopalakrishnan Nair, Kangfu Mei, Vishal M Patel
arXiv 2022. [Paper]
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Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models
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29 Jul 2022
DDSP-based Singing Vocoders: A New Subtractive-based Synthesizer and A Comprehensive Evaluation
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9 Aug 2022
ProDiff: Progressive Fast Diffusion Model For High-Quality Text-to-Speech
Rongjie Huang1, Zhou Zhao, Huadai Liu1, Jinglin Liu, Chenye Cui, Yi Ren
arXiv 2022. [Paper] [Project]
13 Jul 2022
Adversarial Audio Synthesis with Complex-valued Polynomial Networks
Yongtao Wu, Grigorios G Chrysos, Volkan Cevher
arXiv 2022. [Paper]
14 Jun 2022
BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis
Yichong Leng, Zehua Chen, Junliang Guo, Haohe Liu, Jiawei Chen, Xu Tan, Danilo Mandic, Lei He, Xiang-Yang Li, Tao Qin, Sheng Zhao, Tie-Yan Liu
NeurIPS 2022. [Paper] [Github]
30 May 2022
FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech Synthesis
Rongjie Huang1, Max W. Y. Lam1, Jun Wang, Dan Su, Dong Yu, Yi Ren, Zhou Zhao
IJCAI 2022. [Paper] [Project] [Github]
21 Apr 2022
SpecGrad: Diffusion Probabilistic Model based Neural Vocoder with Adaptive Noise Spectral Shaping
Yuma Koizumi, Heiga Zen, Kohei Yatabe, Nanxin Chen, Michiel Bacchiani
arXiv 2022. [Paper]
31 Mar 2022
BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis
Max W. Y. Lam, Jun Wang, Dan Su, Dong Yu
ICLR 2022. [Paper] [Github]
25 Mar 2022
ItôWave: Itô Stochastic Differential Equation Is All You Need For Wave Generation
Shoule Wu1, Ziqiang Shi1
CoRR 2022. [Paper] [Project]
29 Jan 2022
Itô-Taylor Sampling Scheme for Denoising Diffusion Probabilistic Models using Ideal Derivatives
Hideyuki Tachibana, Mocho Go, Muneyoshi Inahara, Yotaro Katayama, Yotaro Watanabe
arXiv 2021. [Paper]
26 Dec 2021
Denoising Diffusion Gamma Models
Eliya Nachmani1, Robin San Roman1, Lior Wolf
arXiv 2021. [Paper]
10 Oct 2021
Variational Diffusion Models
Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho
NeurIPS 2021. [Paper] [Github]
1 Jul 2021
CRASH: Raw Audio Score-based Generative Modeling for Controllable High-resolution Drum Sound Synthesis
Simon Rouard1, Gaëtan Hadjeres1
ISMIR 2021. [Paper] [Project]
14 Jun 2021
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Driven Adaptive Prior
Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu
ICLR 2022. [Paper] [Project]
11 Jun 2021
ItôTTS and ItôWave: Linear Stochastic Differential Equation Is All You Need For Audio Generation
Shoule Wu1, Ziqiang Shi1
arXiv 2022. [Paper] [Project]
17 May 2021
DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism
Jinglin Liu1, Chengxi Li1, Yi Ren1, Feiyang Chen, Peng Liu, Zhou Zhao
AAAI 2022. [Paper] [Project] [Github]
6 May 2021
Symbolic Music Generation with Diffusion Models
Gautam Mittal, Jesse Engel, Curtis Hawthorne, Ian Simon
ISMIR 2021. [Paper] [Github]
30 Mar 2021
DiffWave: A Versatile Diffusion Model for Audio Synthesis
Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, Bryan Catanzaro
ICLR 2021 [Paper] [Github]
21 Sep 2020
WaveGrad: Estimating Gradients for Waveform Generation
Nanxin Chen, Yu Zhang, Heiga Zen, Ron J. Weiss, Mohammad Norouzi, William Chan
ICLR 2021. [Paper] [Project] [Github]
2 Sep 2020
DiffSVC: A Diffusion Probabilistic Model for Singing Voice Conversion
Songxiang Liu1, Yuewen Cao1, Dan Su, Helen Meng
IEEE 2021. [Paper] [Github]
28 May 2021
Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme
Vadim Popov, Ivan Vovk, Vladimir Gogoryan, Tasnima Sadekova, Mikhail Kudinov, Jiansheng Wei
ICLR 2022. [Paper] [Project]
28 Sep 2021
Speech Enhancement and Dereverberation with Diffusion-based Generative Models
Julius Richter, Simon Welker, Jean-Marie Lemercier, Bunlong Lay, Timo Gerkmann
arXiv 2022. [Paper] [Project] [Github]
11 Aug 2022
NU-Wave 2: A General Neural Audio Upsampling Model for Various Sampling Rates
Seungu Han, Junhyeok Lee
arXiv 2022. [Paper] [Project]
17 Jun 2022
Universal Speech Enhancement with Score-based Diffusion
Joan Serrà, Santiago Pascual, Jordi Pons, R. Oguz Araz, Davide Scaini
arXiv 2022. [Paper]
7 Jun 2022
Conditional Diffusion Probabilistic Model for Speech Enhancement
Yen-Ju Lu, Zhong-Qiu Wang, Shinji Watanabe, Alexander Richard, Cheng Yu, Yu Tsao
IEEE 2022. [Paper] [Github]
10 Feb 2022
A Study on Speech Enhancement Based on Diffusion Probabilistic Model
Yen-Ju Lu1, Yu Tsao1, Shinji Watanabe
arXiv 2021. [Paper]
25 Jul 2021
Restoring degraded speech via a modified diffusion model
Jianwei Zhang, Suren Jayasuriya, Visar Berisha
Interspeech 2021. [Paper]
22 Apr 2021
NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling
Junhyeok Lee, Seungu Han
Interspeech 2021. [Paper] [Project] [Github]
6 Apr 2021
WaveFit: An Iterative and Non-autoregressive Neural Vocoder based on Fixed-Point Iteration
Yuma Koizumi, Kohei Yatabe, Heiga Zen, Michiel Bacchiani
arXiv 2022. [Paper] [Project]
3 Oct 2022
Diffsound: Discrete Diffusion Model for Text-to-sound Generation
Dongchao Yang, Jianwei Yu, Helin Wang, Wen Wang, Chao Weng, Yuexian Zou, Dong Yu
arXiv 2022. [Paper] [Project]
20 Jul 2022
Zero-Shot Voice Conditioning for Denoising Diffusion TTS Models
Alon Levkovitch, Eliya Nachmani, Lior Wolf
arXiv 2022. [Paper] [Project]
5 Jun 2022
Guided-TTS 2: A Diffusion Model for High-quality Adaptive Text-to-Speech with Untranscribed Data
Sungwon Kim1, Heeseung Kim1, Sungroh Yoon
arXiv 2022. [Paper] [Project]
30 May 2022
InferGrad: Improving Diffusion Models for Vocoder by Considering Inference in Training
Zehua Chen, Xu Tan, Ke Wang, Shifeng Pan, Danilo Mandic, Lei He, Sheng Zhao
ICASSP 2022. [Paper]
8 Feb 2022
DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs
Songxiang Liu, Dan Su, Dong Yu
arXiv 2022. [Paper] [Github]
28 Jan 2022
Guided-TTS:Text-to-Speech with Untranscribed Speech
Heeseung Kim, Sungwon Kim, Sungroh Yoon
ICML 2021. [Paper]
32 Nov 2021
EdiTTS: Score-based Editing for Controllable Text-to-Speech
Jaesung Tae1, Hyeongju Kim1, Taesu Kim
arXiv 2021. [Paper] [Project] [Github]
6 Oct 2021
WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis
Nanxin Chen, Yu Zhang, Heiga Zen, Ron J. Weiss, Mohammad Norouzi, Najim Dehak, William Chan
arXiv 2021. [Paper] [Project] [Github] [Github2]
17 Jun 2021
Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech
Vadim Popov1, Ivan Vovk1, Vladimir Gogoryan, Tasnima Sadekova, Mikhail Kudinov
ICML 2021. [Paper] [Project] [Github]
13 May 2021
DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism
Jinglin Liu1, Chengxi Li1, Yi Ren1, Feiyang Chen, Peng Liu, Zhou Zhao
arXiv 2021. [Paper] [Project] [Github]
6 May 2021
Diff-TTS: A Denoising Diffusion Model for Text-to-Speech
Myeonghun Jeong, Hyeongju Kim, Sung Jun Cheon, Byoung Jin Choi, Nam Soo Kim
Interspeech 2021. [Paper]
3 Apr 2021
Mandarin Singing Voice Synthesis with Denoising Diffusion Probabilistic Wasserstein GAN
Yin-Ping Cho, Yu Tsao, Hsin-Min Wang, Yi-Wen Liu
arXiv 2022. [Paper] [Project]
21 Sep 2022
Instrument Separation of Symbolic Music by Explicitly Guided Diffusion Model
Sangjun Han, Hyeongrae Ihm, DaeHan Ahn, Woohyung Lim
arXiv 2022. [Paper]
5 Sep 2022
Multi-instrument Music Synthesis with Spectrogram Diffusion
Curtis Hawthorne, Ian Simon, Adam Roberts, Neil Zeghidour, Josh Gardner, Ethan Manilow, Jesse Engel
ISMIR 2022. [Paper]
11 Jun 2022
Structured Denoising Diffusion Models in Discrete State-Spaces
Jacob Austin1, Daniel D. Johnson1, Jonathan Ho, Daniel Tarlow, Rianne van den Berg
NeurIPS 2021. [Paper]
7 Jul 2021
Latent Diffusion Energy-Based Model for Interpretable Text Modeling
Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruigi Gao, Yixin Zhu, Song-Chun Zhu, Ying Nian Wu
ICML 2022. [Paper] [Github]
13 Jun 2022
Diffusion-LM Improves Controllable Text Generation
Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B. Hashimoto
NeurIPS 2022. [Paper] [Github]
27 May 2022
Zero-Shot Translation using Diffusion Models
Eliya Nachmani1, Shaked Dovrat1
arXiv 2021. [Paper]
2 Nov 2021
TabDDPM: Modelling Tabular Data with Diffusion Models
Akim Kotelnikov, Dmitry Baranchuk, Ivan Rubachev, Artem Babenko
arXiv 2022. [Paper] [Github]
30 Sep 2022
Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models
Juan Miguel Lopez Alcaraz, Nils Strodthoff
arXiv 2022. [Paper] [Github]
19 Aug 2022
ScoreGrad: Multivariate Probabilistic Time Series Forecasting with Continuous Energy-based Generative Models
Tijin Yan, Hongwei Zhang, Tong Zhou, Yufeng Zhan, Yuanqing Xia
arXiv 2021. [Paper] [Github]
18 Jun 2021
Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting
Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf
ICLR 2021. [Paper] [Github]
2 Feb 2021
Neural Markov Controlled SDE: Stochastic Optimization for Continuous-Time Data
Sung Woo Park, Kyungjae Lee, Junseok Kwon
ICLR 2022. [Paper]
29 Sep 2021
Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models
Juan Miguel Lopez Alcaraz, Nils Strodthoff
arXiv 2022. [Paper] [Github]
19 Aug 2022
CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation
Yusuke Tashiro, Jiaming Song, Yang Song, Stefano Ermon
NeurIPS 2021. [Paper] [Github]
7 Jul 2021
Diffusion Models for Graphs Benefit From Discrete State Spaces
Kilian Konstantin Haefeli, Karolis Martinkus, Nathanaël Perraudin, Roger Wattenhofer
NeurIPS 2022. [Paper]
4 Oct 2022
DiGress: Discrete Denoising diffusion for graph generation
Clement Vignac1, Igor Krawczuk1, Antoine Siraudin, Bohan Wang, Volkan Cevher, Pascal Frossard
arXiv 2022. [Paper]
29 Sep 2022
Permutation Invariant Graph Generation via Score-Based Generative Modeling
Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, Stefano Ermon
AISTATS 2021. [Paper] [Github]
2 Mar 2020
Dynamic-Backbone Protein-Ligand Structure Prediction with Multiscale Generative Diffusion Models
Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Anima Anandkumar
arXiv 2022. [Paper]
30 Sep 2022
Equivariant Energy-Guided SDE for Inverse Molecular Design
Fan Bao1, Min Zhao1, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu
arXiv 2022. [Paper]
30 Sep 2022
Protein structure generation via folding diffusion
Kevin E. Wu, Kevin K. Yang, Rianne van den Berg, James Y. Zou, Alex X. Lu, Ava P. Amini
arXiv 2022. [Paper]
30 Sep 2022
MDM: Molecular Diffusion Model for 3D Molecule Generation
Lei Huang, Hengtong Zhang, Tingyang Xu, Ka-Chun Wong
arXiv 2022. [Paper]
13 Sep 2022
Diffusion-based Molecule Generation with Informative Prior Bridges
Lemeng Wu1, Chengyue Gong1, Xingchao Liu, Mao Ye, Qiang Liu
NeurIPS 2022. [Paper]
2 Sep 2022
Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models
Shitong Luo1, Yufeng Su1, Xingang Peng, Sheng Wang, Jian Peng, Jianzhu Ma
BioRXiv 2022. [Paper]
11 July 2022
Data-driven discovery of novel 2D materials by deep generative models
Peder Lyngby, Kristian Sommer Thygesen
arXiv 2022. [Paper]
24 Jun 2022
Score-based Generative Models for Calorimeter Shower Simulation
Vinicius Mikuni, Benjamin Nachman
arXiv 2022. [Paper]
17 Jun 2022
Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem
Brian L. Trippe1, Jason Yim1, Doug Tischer, Tamara Broderick, David Baker, Regina Barzilay, Tommi Jaakkola
CoRR 2022. [Paper]
8 Jun 2022'
Torsional Diffusion for Molecular Conformer Generation
Bowen Jing, Gabriele Corso, Regina Barzilay, Tommi S. Jaakkola
ICLR Workshop 2022. [Paper] [Github]
1 Jun 2022
Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models
Namrata Anand, Tudor Achim
arXiv 2022. [Paper] [Project] [Github]
26 May 2022
A Score-based Geometric Model for Molecular Dynamics Simulations
Fang Wu1, Qiang Zhang1, Xurui Jin, Yinghui Jiang, Stan Z. Li
CoRR 2022. [Paper]
19 Apr 2022
Equivariant Diffusion for Molecule Generation in 3D
Emiel Hoogeboom1, Victor Garcia Satorras1, Clément Vignac, Max Welling
ICML 2022. [Paper] [Github]
31 Mar 2022
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation
Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang
ICLR 2022. [Paper] [Github]
6 Mar 2022
Crystal Diffusion Variational Autoencoder for Periodic Material Generation
Tian Xie1, Xiang Fu1, Octavian-Eugen Ganea1, Regina Barzilay, Tommi Jaakkola
NeurIPS 2021. [Paper] [Github]
12 Oct 2021
Predicting Molecular Conformation via Dynamic Graph Score Matching
Shitong Luo, Chence Shi, Minkai Xu, Jian Tang
NeurIPS 2021. [Paper]
22 May 2021
Analyzing Diffusion as Serial Reproduction
Raja Marjieh, Ilia Sucholutsky, Thomas A. Langlois, Nori Jacoby, Thomas L. Griffiths
arXiv 2022. [Paper]
29 Sep 2022
Convergence of score-based generative modeling for general data distributions
Holden Lee, Jianfeng Lu, Yixin Tan
arXiv 2022. [Paper]
26 Sep 2022
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions
Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru R. Zhang
arXiv 2022. [Paper]
22 Sep 2022
Riemannian Diffusion Models
Chin-Wei Huang, Milad Aghajohari, Avishek Joey Bose, Prakash Panangaden, Aaron Courville
NeurIPS 2022. [Paper]
16 Aug 2022
Convergence of denoising diffusion models under the manifold hypothesis
Valentin De Bortoli
arXiv 2022. [Paper]
10 Aug 2022
Theory and Algorithms for Diffusion Processes on Riemannian Manifolds
Bowen Jing, Gabriele Corso, Jeffrey Chang, Regina Barzilay, Tommi Jaakkola
arXiv 2022. [Paper] [Github]
1 Jun 2022
Riemannian Score-Based Generative Modeling
Valentin De Bortoli1, Emile Mathieu1, Michael Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet
arXiv 2022. [Paper]
6 Feb 2022
Interpreting diffusion score matching using normalizing flow
Wenbo Gong1, Yingzhen Li1
ICML Workshop 2021. [Paper]
21 Jul 2021
A Connection Between Score Matching and Denoising Autoencoders
Pascal Vincent
Neural Computation 2011. [Paper]
7 Jul 2011
Bayesian Learning via Stochastic Gradient Langevin Dynamics
Max Welling, Yee Whye Teh
ICML 2011. [Paper] [Github]
20 Apr 2022
DALL-E-Bot: Introducing Web-Scale Diffusion Models to Robotics
Ivan Kapelyukh, Vitalis Vosylius, Edward Johns
arXiv 2022. [Paper]
5 Oct 2022
Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling
Huayu Chen, Cheng Lu, Chengyang Ying, Hang Su, Jun Zhu
arXiv 2022. [Paper]
29 Sep 2022
Denoising Diffusion Error Correction Codes
Yoni Choukroun, Lior Wolf
arXiv 2022. [Paper]
16 Sep 2022
A Diffusion Model Predicts 3D Shapes from 2D Microscopy Images
Dominik J. E. Waibel, Ernst Röell, Bastian Rieck, Raja Giryes, Carsten Marr
arXiv 2022. [Paper]
30 Aug 2022
Vector Quantized Diffusion Model with CodeUnet for Text-to-Sign Pose Sequences Generation
Pan Xie, Qipeng Zhang, Zexian Li, Hao Tang, Yao Du, Xiaohui Hu
arXiv 2022. [Paper]
19 Aug 2022
TopoDiff: A Performance and Constraint-Guided Diffusion Model for Topology Optimization
François Mazé, Faez Ahmed
arXiv 2022. [Paper]
20 Aug 2022
DeScoD-ECG: Deep Score-Based Diffusion Model for ECG Baseline Wander and Noise Removal
Huayu Li, Gregory Ditzler, Janet Roveda, Ao Li
arXiv 2022. [Paper]
31 Jul 2022
Recommendation via Collaborative Diffusion Generative Model
Joojo Walker, Ting Zhong, Fengli Zhang, Qiang Gao, Fan Zhou
KSEM 2022. [Paper]
19 Jul 2022
Discrete Contrastive Diffusion for Cross-Modal and Conditional Generation
Ye Zhu, Yu Wu, Kyle Olszewski, Jian Ren, Sergey Tulyakov, Yan Yan
arXiv 2022. [Paper] [Project] [Github]
15 Jun 2022
CARD: Classification and Regression Diffusion Models
Xizewen Han1, Huangjie Zheng1, Mingyuan Zhou
NeurIPS 2022. [Paper]
15 Jun 2022
Neural Diffusion Processes
Vincent Dutordoir, Alan Saul, Zoubin Ghahramani, Fergus Simpson
arXiv 2022. [Paper]
8 Jun 2022
Deep Diffusion Models for Robust Channel Estimation
Marius Arvinte, Jonathan I Tamir
arXiv 2021. [Paper] [Github]
16 Nov 2021
Deep diffusion-based forecasting of COVID-19 by incorporating network-level mobility information
Padmaksha Roy, Shailik Sarkar, Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu
ASONAM 2021. [Paper]
9 Nov 2021
Realistic galaxy image simulation via score-based generative models
Michael J. Smith (Hertfordshire), James E. Geach, Ryan A. Jackson, Nikhil Arora, Connor Stone, Stéphane Courteau
MNRAS 2022. [Paper]
2 Nov 2021
Diffusion models for Handwriting Generation
Troy Luhman1, Eric Luhman1
arXiv 2020. [Paper] [Github]
13 Nov 2020