This repository contains a collection of resources and papers on Diffusion Models and Score-matching Models.
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
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
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
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
arXiv 2022. [Paper]
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]
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
arXiv 2022. [Paper]
2 Jun 2022
Elucidating the Design Space of Diffusion-Based Generative Models
Tero Karras, Miika Aittala, Timo Aila, Samuli Laine
arXiv 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
arXiv 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
arXiv 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
arXiv 2021. [Paper]
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
arXiv 2021. [Paper] [Project]
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
arXiv 2021. [Paper]
7 Jul 2021
Variational Diffusion Models
Diederik P. Kingma1, Tim Salimans1, Ben Poole, Jonathan Ho
arXiv 2021. [Paper] [Github]
1 Jul 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
ICML Workshop 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
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
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
Diffusion models as plug-and-play priors
Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras
arXiv 2022. [Paper]
17 June 2022
Diffusion Models for Implicit Image Segmentation Ensembles
Julia Wolleb1, Robin Sandkühler1, Florentin Bieder, Philippe Valmaggia, Philippe C. Cattin
arXiv 2021. [Paper]
6 Dec 2021
Label-Efficient Semantic Segmentation with Diffusion Models
Dmitry Baranchuk, Ivan Rubachev, Andrey Voynov, Valentin Khrulkov, Artem Babenko
arXiv 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
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
Pretraining is All You Need for Image-to-Image Translation
Tengfei Wang, Ting Zhang, Bo Zhang, Hao Ouyang, Dong Chen, Qifeng Chen, Fang Wen
arXiv 2022. [Paper] [Project] [Github]
25 May 2022
VQBB: Image-to-image Translation with Vector Quantized Brownian Bridge
Bo Li, Kaitao Xue, Bin Liu, Yu-Kun Lai
arXiv 2022. [Paper]
16 May 2022
The Swiss Army Knife for Image-to-Image Translation: Multi-Task Diffusion Models
Julia Wolleb1, Robin Sandkühler1, Florentin Bieder, Philippe C. Cattin
arXiv 2022. [Paper]
6 Apr 2022
Dual Diffusion Implicit Bridges for Image-to-Image Translation
Xuan Su, Jiaming Song, Chenlin Meng, Stefano Ermon
arXiv 2022. [Paper]
16 Mar 2022
Denoising Diffusion Restoration Models
Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song
arXiv 2022. [Paper]
27 Jan 2022
DiffuseMorph: Unsupervised Deformable Image Registration Along Continuous Trajectory Using Diffusion Models
Boah Kim, Inhwa Han, Jong Chul Ye
arXiv 2021. [Paper]
9 Dec 2021
Diffusion Autoencoders: Toward a Meaningful and Decodable Representation
Konpat Preechakul, Nattanat Chatthee, Suttisak Wizadwongsa, Supasorn Suwajanakorn
arXiv 2021. [Paper] [Project]
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
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
UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Models
Hiroshi Sasaki, Chris G. Willcocks, Toby P. Breckon
arXiv 2021. [Paper]
12 Apr 2021
Denoising Diffusion Restoration Models
Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song
arXiv 2022. [Paper]
27 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
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
Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction
Hyungjin Chung, Byeongsu Sim, Jong Chul Ye
arXiv 2021. [Paper]
9 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
S3RP: Self-Supervised Super-Resolution and Prediction for Advection-Diffusion Process
Chulin Wang, Kyongmin Yeo, Xiao Jin, Andres Codas, Levente J. Klein, Bruce Elmegreen
arXiv 2021. [Paper]
8 Nov 2021
Autoregressive Diffusion Models
Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, Tim Salimans
arXiv 2021. [Paper]
5 Oct 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
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
SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Models
Haoying Li, Yifan Yang, Meng Chang, Huajun Feng, Zhihai Xu, Qi Li, Yueting Chen
arXiv 2021. [Paper]
30 Apr 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
Blended Latent Diffusion
Omri Avrahami, Ohad Fried, Dani Lischinski
ACM 2022. [Paper] [Project] [Github]
6 Jun 2022
Improving Diffusion Models for Inverse Problems using Manifold Constraints
Hyungjin Chung1, Byeongsu Sim1, Dohoon Ryu, Jong Chul Ye
arXiv 2022. [Paper]
2 Jun 2022
DiVAE: Photorealistic Images Synthesis with Denoising Diffusion Decoder
Jie Shi1, Chenfei Wu1, Jian Liang, Xiang Liu, Nan Duan
arXiv 2022. [Paper]
1 Jun 2022
Denoising Diffusion Restoration Models
Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song
arXiv 2022. [Paper]
27 Jan 2022
RePaint: Inpainting using Denoising Diffusion Probabilistic Models
Andreas Lugmayr, Martin Danelljan, Andres Romero, Fisher Yu, Radu Timofte, Luc Van Gool
arXiv 2022. [Paper] [Github]
24 Jan 2022
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
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
Zhisheng Xiao, Karsten Kreis, Arash Vahdat
arXiv 2021. [Paper] [Project]
15 Dec 2021
Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction
Hyungjin Chung, Byeongsu Sim, Jong Chul Ye
arXiv 2021. [Paper]
9 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
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
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
Blended Latent Diffusion
Omri Avrahami, Ohad Fried, Dani Lischinski
ACM 2022. [Paper] [Project] [Github]
6 Jun 2022
Compositional Visual Generation with Composable Diffusion Models
Nan Liu1, Shuang Li1, Yilun Du1, Antonio Torralba, Joshua B. Tenenbaum
arXiv 2022. [Paper] [Project]
3 Jun 2022
DiVAE: Photorealistic Images Synthesis with Denoising Diffusion Decoder
Jie Shi1, Chenfei Wu1, Jian Liang, Xiang Liu, Nan Duan
arXiv 2022. [Paper]
1 Jun 2022
Improved Vector Quantized Diffusion Models
Zhicong Tang, Shuyang Gu, Jianmin Bao, Dong Chen, Fang Wen
arXiv 2022. [Paper] [Github]
31 May 2022
Text2Human: Text-Driven Controllable Human Image Generation
Yuming Jiang, Shuai Yang, Haonan Qiu, Wayne Wu, Chen Change Loy, Ziwei Liu
ACM 2022. [Paper]
31 May 2022
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
Chitwan Saharia1, William Chan1, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J Fleet, Mohammad Norouzi
arXiv 2022. [Paper]
23 May 2022
Retrieval-Augmented Diffusion Models
Andreas Blattmann1, Robin Rombach1, Kaan Oktay, Björn Ommer
arXiv 2022. [Paper]
25 Apr 2022
Hierarchical Text-Conditional Image Generation with CLIP Latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, Mark Chen
arXiv 2022. [Paper]
13 Apr 2022
KNN-Diffusion: Image Generation via Large-Scale Retrieval
Oron Ashual, Shelly Sheynin, Adam Polyak, Uriel Singer, Oran Gafni, Eliya Nachmani, Yaniv Taigman
arXiv 2022. [Paper]
6 Apr 2022
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
Vector Quantized Diffusion Model for Text-to-Image Synthesis
Shuyang Gu, Dong Chen, Jianmin Bao, Fang Wen, Bo Zhang, Dongdong Chen, Lu Yuan, Baining Guo
CVPR 2022. [Paper] [Github]
29 Nov 2021
Blended Diffusion for Text-driven Editing of Natural Images
Omri Avrahami, Dani Lischinski, Ohad Fried
CVPR 2022. [Paper] [Project] [Github]
29 Nov 2021
DiffusionCLIP: Text-guided Image Manipulation Using Diffusion Models
Gwanghyun Kim, Jong Chul Ye
CVPR 2022. [Paper]
6 Oct 2021
A Novel Unified Conditional Score-based Generative Framework for Multi-modal Medical Image Completion
Xiangxi Meng, Yuning Gu, Yongsheng Pan, Nizhuan Wang, Peng Xue, Mengkang Lu, Xuming He, Yiqiang Zhan, Dinggang Shen
arXiv 2022. [Paper]
7 Jul 2022
Cross-Modal Transformer GAN: A Brain Structure-Function Deep Fusing Framework for Alzheimer's Disease
Junren Pan, Shuqiang Wang
arXiv 2022. [Paper]
20 Jun 2022
Diffusion Deformable Model for 4D Temporal Medical Image Generation
Boah Kim, Jong Chul Ye
arXiv 2022. [Paper]
27 Jun 2022
Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models
Walter H. L. Pinaya, Mark S. Graham, Robert Gray, Pedro F Da Costa, Petru-Daniel Tudosiu, Paul Wright, Yee H. Mah, Andrew D. MacKinnon, James T. Teo, Rolf Jager, David Werring, Geraint Rees, Parashkev Nachev, Sebastien Ourselin, M. Jorge Cardos
arXiv 2022. [Paper]
7 Jun 2022
Improving Diffusion Models for Inverse Problems using Manifold Constraints
Hyungjin Chung1, Byeongsu Sim1, Dohoon Ryu, Jong Chul Ye
arXiv 2022. [Paper]
2 Jun 2022
The Swiss Army Knife for Image-to-Image Translation: Multi-Task Diffusion Models
Julia Wolleb1, Robin Sandkühler1, Florentin Bieder, Philippe C. Cattin
arXiv 2022. [Paper]
6 Apr 2022
MR Image Denoising and Super-Resolution Using Regularized Reverse Diffusion
Hyungjin Chung, Eun Sun Lee, Jong Chul Ye
arXiv 2022. [Paper]
23 Mar 2022
Diffusion Models for Medical Anomaly Detection
Julia Wolleb, Florentin Bieder, Robin Sandkühler, Philippe C. Cattin
arXiv 2022. [Paper]
8 Mar 2022
Towards performant and reliable undersampled MR reconstruction via diffusion model sampling
Cheng Peng, Pengfei Guo, S. Kevin Zhou, Vishal Patel, Rama Chellappa
arXiv 2022. [Paper]
8 Mar 2022
Measurement-conditioned Denoising Diffusion Probabilistic Model for Under-sampled Medical Image Reconstruction
Yutong Xie, Quanzheng Li
arXiv 2022. [Paper] [Github]
5 Mar 2022
MRI Reconstruction via Data Driven Markov Chain with Joint Uncertainty Estimation
Guanxiong Luo, Martin Heide, Martin Uecker
arXiv 2022. [Paper]
3 Feb 2022
Unsupervised Denoising of Retinal OCT with Diffusion Probabilistic Model
Dewei Hu, Yuankai K. Tao, Ipek Oguz
arXiv 2022. [Paper] [Github]
27 Jan 2022
Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction
Hyungjin Chung, Byeongsu Sim, Jong Chul Ye
CVPR 2021. [Paper]
9 Dec 2021
Solving Inverse Problems in Medical Imaging with Score-Based Generative Models
Yang Song1, Liyue Shen1, Lei Xing, Stefano Ermon
NeurIPS Workshop 2021. [Paper]
15 Nov 2021
Score-based diffusion models for accelerated MRI
Hyungjin Chung, Jong chul Ye
arXiv 2021. [Paper]
8 Oct 2021
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]
23 May 2022
Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation
Vikram Voleti1, Alexia Jolicoeur-Martineau1, Christopher Pal
arXiv 2022. [Paper]
19 May 2022
Video Diffusion Models
Jonathan Ho1, Tim Salimans1, Alexey Gritsenko, William Chan, Mohammad Norouzi, David J. Fleet
arXiv 2022. [Paper]
7 Apr 2022
Diffusion Probabilistic Modeling for Video Generation
Ruihan Yang, Prakhar Srivastava, Stephan Mandt
arXiv 2022. [Paper]
16 Mar 2022
A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion
Zhaoyang Lyu, Zhifeng Kong, Xudong Xu, Liang Pan, Dahua Lin
arXiv 2021. [Paper]
7 Dec 2021
Score-Based Point Cloud Denoising
Shitong Luo, Wei Hu
arXiv 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
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
arXiv 2022. [Paper]
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
arXiv 2022. [Paper] [Project]
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
arXiv 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
arXiv 2021. [Paper] [Github]
1 Jul 2021
CRASH: Raw Audio Score-based Generative Modeling for Controllable High-resolution Drum Sound Synthesis
Simon Rouard1, Gaëtan Hadjeres1
arXiv 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
arXiv 2021. [Paper] [Project]
11 Jun 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
Symbolic Music Generation with Diffusion Models
Gautam Mittal, Jesse Engel, Curtis Hawthorne, Ian Simon
arXiv 2021. [Paper] [Code]
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
arXiv 2021. [Paper] [Github]
28 May 2021
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]
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
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]
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
arXiv 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]
28 Jan 2022
Guided-TTS:Text-to-Speech with Untranscribed Speech
Heeseung Kim, Sungwon Kim, Sungroh Yoon
arXiv 2021. [Paper]
32 Nov 2021
EdiTTS: Score-based Editing for Controllable Text-to-Speech
Jaesung Tae1, Hyeongju Kim1, Taesu Kim
arXiv 2021. [Paper]
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
Back to the Source: Diffusion-Driven Test-Time Adaptation
Jin Gao1, Jialing Zhang1, Xihui Liu, Trevor Darrell, Evan Shelhamer, Dequan Wang
arXiv 2022. [Paper]
7 Jul 2022
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
arXiv 2022. [Paper]
30 May 2022
Diffusion Models for Adversarial Purification
Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar
ICML 2022. [Paper] [Project]
16 May 2022
TFDPM: Attack detection for cyber-physical systems with diffusion probabilistic models
Tijin Yan, Tong Zhou, Yufeng Zhan, Yuanqing Xia
arXiv 2021. [Paper]
20 Dec 2021
Adversarial purification with Score-based generative models
Jongmin Yoon, Sung Ju Hwang, Juho Lee
ICML 2021. [Paper] [Github]
11 Jun 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]
13 Jun 2022
Diffusion-LM Improves Controllable Text Generation
Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B. Hashimoto
arXiv 2022. [Paper]
27 May 2022
Zero-Shot Translation using Diffusion Models
Eliya Nachmani1, Shaked Dovrat1
arXiv 2021. [Paper]
2 Nov 2021
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
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
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
arXiv 2022. [Paper]
8 Jun 2022
Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models
Namrata Anand, Tudor Achim
arXiv 2022. [Paper] [Project]
26 May 2022
A Score-based Geometric Model for Molecular Dynamics Simulations
Fang Wu1, Qiang Zhang1, Xurui Jin, Yinghui Jiang, Stan Z. Li
arXiv 2022. [Paper]
19 Apr 2022
Equivariant Diffusion for Molecule Generation in 3D
Emiel Hoogeboom1, Victor Garcia Satorras1, Clément Vignac, Max Welling
arXiv 2022. [Paper]
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]
6 Mar 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
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
CARD: Classification and Regression Diffusion Models
Xizewen Han1, Huangjie Zheng1, Mingyuan Zhou
arXiv 2022. [Paper]
15 Jun 2022
Multi-instrument Music Synthesis with Spectrogram Diffusion
Curtis Hawthorne, Ian Simon, Adam Roberts, Neil Zeghidour, Josh Gardner, Ethan Manilow, Jesse Engel
arXiv 2022. [Paper]
11 Jun 2022
Neural Diffusion Processes
Vincent Dutordoir, Alan Saul, Zoubin Ghahramani, Fergus Simpson
arXiv 2022. [Paper]
8 Jun 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
Planning with Diffusion for Flexible Behavior Synthesis
Michael Janner, Yilun Du, Joshua B. Tenenbaum, Sergey Levine
arxiv 2022. [Paper]
20 May 2022
Stochastic Trajectory Prediction via Motion Indeterminacy Diffusion
Tianpei Gu1, Guangyi Chen1, Junlong Li, Chunze Lin, Yongming Rao, Jie Zhou, Jiwen Lu
arXiv 2022. [Paper]
25 Mar 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
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
arXiv 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
Crystal Diffusion Variational Autoencoder for Periodic Material Generation
Tian Xie1, Xiang Fu1, Octavian-Eugen Ganea1, Regina Barzilay, Tommi Jaakkola
arXiv 2021. [Paper]
12 Oct 2021
Diffusion models for Handwriting Generation
Troy Luhman1, Eric Luhman1
arXiv 2020. [Paper] [Github]
13 Nov 2020
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