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Sliced Score Matching: A Scalable Approach to Density and Score Estimation

May 17, 2019 Yang Song, Sahaj Garg, Jiaxin Shi, Stefano Ermon

methodology, code

Generative Modeling by Estimating Gradients of the Data Distribution

July 12, 2019 Yang Song, Stefano Ermon

classics, methodology, blog, code
  • See also the blogpost
  • Sample from multiple noisy versions of the data distribution
  • First results on popular image datasets
  • Code

Source Separation with Deep Generative Prior

February 19, 2020 Vivek Jayaram, John Thickstun
application

Permutation invariant graph generation via score-based generative modeling

March 02, 2020 Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, Stefano Ermon

application, code

Improved techniques for training score-based generative models

June 16, 2020 Yang Song, Stefano Ermon

performance, code
  • Code
  • Training tricks like exponential moving average (EMA), choosing prior variance etc.

Rethinking the Role of Gradient-Based Attribution Methods for Model Interpretability

June 16, 2020 Suraj Srinivas, Francois Fleuret
methodology

Denoising diffusion probabilistic models

June 19, 2020 Jonathan Ho, Ajay Jain, Pieter Abbeel

classics, variational, code, blog

Efficient Learning of Generative Models via Finite-Difference Score Matching

July 07, 2020 Tianyu Pang, Kun Xu, Chongxuan Li, Yang Song, Stefano Ermon, Jun Zhu
methodology, performance

Learning gradient fields for shape generation

August 14, 2020 Ruojin Cai, Guandao Yang, Hadar Averbuch-Elor, Zekun Hao, Serge Belongie, Noah Snavely, Bharath Hariharan
application

Wavegrad: Estimating gradients for waveform generation

September 02, 2020 Nanxin Chen, Yu Zhang, Heiga Zen, Ron J. Weiss, Mohammad Norouzi, William Chan
application

Adversarial score matching and improved sampling for image generation

September 11, 2020 Alexia Jolicoeur-Martineau, Rémi Piché-Taillefer, Rémi Tachet des Combes, Ioannis Mitliagkas

performance, code, blog

Diffwave: A versatile diffusion model for audio synthesis

September 21, 2020 Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, Bryan Catanzaro
application

Denoising diffusion implicit models

October 06, 2020 Jiaming Song, Chenlin Meng, Stefano Ermon

methodology, code

VoiceGrad: Non-Parallel Any-to-Many Voice Conversion with Annealed Langevin Dynamics

October 06, 2020 Hirokazu Kameoka, Takuhiro Kaneko, Kou Tanaka, Nobukatsu Hojo, Shogo Seki
application

Denoising Score-Matching for Uncertainty Quantification in Inverse Problems

November 16, 2020 Zaccharie Ramzi, Benjamin Remy, Francois Lanusse, Jean-Luc Starck, Philippe Ciuciu
application

Probabilistic Mapping of Dark Matter by Neural Score Matching

November 16, 2020 Benjamin Remy, Francois Lanusse, Zaccharie Ramzi, Jia Liu, Niall Jeffrey, Jean-Luc Starck
application

Score-Based Generative Modeling through Stochastic Differential Equations

November 26, 2020 Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole

classics, methodology, code

Learning energy-based models by diffusion recovery likelihood

December 15, 2020 Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma
methodology

Knowledge distillation in iterative generative models for improved sampling speed

January 07, 2021 Eric Luhman, Troy Luhman
performance

Maximum likelihood training of score-based diffusion models

January 22, 2021 Yang Song, Conor Durkan, Iain Murray, Stefano Ermon

theory,variational
  • Write the Kullback-Leibler divergence between true reverse process and approximation
  • Derive ELBO approximation for MLE estimation

Stochastic Image Denoising by Sampling from the Posterior Distribution

January 23, 2021 Bahjat Kawar, Gregory Vaksman, Michael Elad
methodology, application

Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting

January 28, 2021 Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf
application

Argmax flows and multinomial diffusion: Towards non-autoregressive language models

February 10, 2021 Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling
methodology

Improved denoising diffusion probabilistic models

February 18, 2021 Alex Nichol, Prafulla Dhariwal

performance, code
  • Code
  • Architecture improvements, simpler than previous networks, cosine schedule

Diffusion Probabilistic Models for 3D Point Cloud Generation

March 02, 2021 Shitong Luo, Wei Hu
methodology

Symbolic music generation with diffusion models

March 30, 2021 Gautam Mittal, Jesse Engel, Curtis Hawthorne, Ian Simon
application

NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling

April 06, 2021 Junhyeok Lee, Seungu Han
application

Noise Estimation for Generative Diffusion Models

April 06, 2021 Robin San-Roman, Eliya Nachmani, Lior Wolf
methodology

3D Shape Generation and Completion through Point-Voxel Diffusion

April 08, 2021 Linqi Zhou, Yilun Du, Jiajun Wu
methodology

On tuning consistent annealed sampling for denoising score matching

April 08, 2021 Joan Serrà, Santiago Pascual, Jordi Pons
methodology

UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Models

April 12, 2021 Hiroshi Sasaki, Chris G. Willcocks, Toby P. Breckon
application

Image super-resolution via iterative refinement

April 15, 2021 Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi
performance

DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism

May 06, 2021 Jinglin Liu, Chengxi Li, Yi Ren, Feiyang Chen, Zhou Zhao
application

Learning Gradient Fields for Molecular Conformation Generation

May 09, 2021 Chence Shi, Shitong Luo, Minkai Xu, Jian Tang
methodology, application

Diffusion models beat gans on image synthesis

May 11, 2021 Prafulla Dhariwal, Alex Nichol

performance, code

Grad-tts: A diffusion probabilistic model for text-to-speech

May 13, 2021 Vadim Popov, Ivan Vovk, Vladimir Gogoryan, Tasnima Sadekova, Mikhail Kudinov
application

DiffSVC: A Diffusion Probabilistic Model for Singing Voice Conversion

May 28, 2021 Songxiang Liu, Yuewen Cao, Dan Su, Helen Meng
application

Gotta Go Fast When Generating Data with Score-Based Models

May 28, 2021 Alexia Jolicoeur-Martineau, Ke Li, Rémi Piché-Taillefer, Tal Kachman, Ioannis Mitliagkas

performance, code, blog

Representation Learning in Continuous-Time Score-Based Generative Models

May 29, 2021 Korbinian Abstreiter, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou
methodology

Cascaded Diffusion Models for High Fidelity Image Generation

May 30, 2021 Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans

performance, application, blog

SNIPS: Solving Noisy Inverse Problems Stochastically

May 31, 2021 Bahjat Kawar, Gregory Vaksman, Michael Elad
methodology, application

On Fast Sampling of Diffusion Probabilistic Models

May 31, 2021 Zhifeng Kong, Wei Ping
performance

Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling

June 01, 2021 Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet

methodology, optimal transport, theory, blog
  • See also the blogpost
  • Approximates solution to Schrodinger bridge problem by approximiating iterative reverse diffusions with score/drift networks
  • Theoretical results on quality of generative distribution
  • Code

A Variational Perspective on Diffusion-Based Generative Models and Score Matching

June 05, 2021 Chin-Wei Huang, Jae Hyun Lim, Aaron Courville
theory, variational

Learning to Efficiently Sample from Diffusion Probabilistic Models

June 07, 2021 Daniel Watson, Jonathan Ho, Mohammad Norouzi, William Chan
performance

Score Matching Model for Unbounded Data Score

June 10, 2021 Dongjun Kim, Seungjae Shin, Kyungwoo Song, Wanmo Kang, Il-Chul Moon
methodology

Score-based Generative Modeling in Latent Space

June 10, 2021 Arash Vahdat, Karsten Kreis, Jan Kautz
methodology

Adversarial purification with Score-based generative models

June 11, 2021 Jongmin Yoon, Sung Ju Hwang, Juho Lee
application

PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Driven Adaptive Prior

June 11, 2021 Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu
performance

D2C: Diffusion-Denoising Models for Few-shot Conditional Generation

June 12, 2021 Abhishek Sinha, Jiaming Song, Chenlin Meng, Stefano Ermon
application

CRASH: Raw Audio Score-based Generative Modeling for Controllable High-resolution Drum Sound Synthesis

June 14, 2021 Simon Rouard, Gaëtan Hadjeres
application

Non Gaussian Denoising Diffusion Models

June 14, 2021 Eliya Nachmani, Robin San Roman, Lior Wolf
methodology

ScoreGrad: Multivariate Probabilistic Time Series Forecasting with Continuous Energy-based Generative Models

June 18, 2021 Tijin Yan, Hongwei Zhang, Tong Zhou, Yufeng Zhan, Yuanqing Xia
application

Deep Generative Learning via Schrödinger Bridge

June 19, 2021 Gefei Wang, Yuling Jiao, Qian Xu, Yang Wang, Can Yang
methodology, optimal transport

Diffusion Priors in Variational Autoencoders

June 29, 2021 Antoine Wehenkel, Gilles Louppe
methodology

Variational Diffusion Models

July 01, 2021 Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho

variational, methodology
  • Main contribution seems to be alternative parameterization of the marginals of forward SDE in terms of SNR, then decreasing SNR function is optimized in the ELBO

GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation

September 29, 2021 Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang
methodology, application

Predicting Molecular Conformation via Dynamic Graph Score Matching

January 12, 2021 Shitong Luo, Chence Shi, Minkai Xu, Jian Tang
methodology, application

Structured Denoising Diffusion Models in Discrete State-Spaces

July 07, 2021 Jacob Austin, Daniel D. Johnson, Jonathan Ho, Daniel Tarlow, Rianne van den Berg
methodology

CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation

July 07, 2021 Yusuke Tashiro, Jiaming Song, Yang Song, Stefano Ermon
application

Denoising diffusion probabilistic models for replica exchange

July 15, 2021 Yihang Wang, Lukas Herron, Pratyush Tiwary
application

Beyond In-Place Corruption: Insertion and Deletion in Denoising Probabilistic Models

July 16, 2021 Daniel D. Johnson, Jacob Austin, Rianne van den Berg, Daniel Tarlow
methodology

Interpreting diffusion score matching using normalizing flow

July 21, 2021 Wenbo Gong, Yingzhen Li
methodology

Score-Based Point Cloud Denoising

July 23, 2021 Shitong Luo, Wei Hu
methodology

SDEdit: Image Synthesis and Editing with Stochastic Differential Equations

August 02, 2021 Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, Stefano Ermon
methodology, application

Robust Compressed Sensing MRI with Deep Generative Priors

August 03, 2021 Ajil Jalal, Marius Arvinte, Giannis Daras, Eric Price, Alexandros G. Dimakis, Jonathan I. Tamir
application

IVLR: Conditioning Method for Denoising Diffusion Probabilistic Models

August 06, 2021 Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, Sungroh Yoon
application

ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis

August 19, 2021 Patrick Esser, Robin Rombach, Andreas Blattmann, Björn Ommer
application

Bilateral Denoising Diffusion Models

August 26, 2021 Max W. Y. Lam, Jun Wang, Rongjie Huang, Dan Su, Dong Yu
methodology

Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme

September 28, 2021 Vadim Popov, Ivan Vovk, Vladimir Gogoryan, Tasnima Sadekova, Mikhail Kudinov, Jiansheng Wei
application

Score-Based Generative Classifiers

October 01, 2021 Roland S. Zimmermann, Lukas Schott, Yang Song, Benjamin A. Dunn, David A. Klindt
methodology

Autoregressive Diffusion Models

October 05, 2021 Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, Tim Salimans
methodology

Score-based Generative Neural Networks for Large-Scale Optimal Transport

October 07, 2021 Max Daniels, Tyler Maunu, Paul Hand
methodology

Score-based diffusion models for accelerated MRI

October 08, 2021 Hyungjin Chung, Jong Chul Ye
application

Crystal Diffusion Variational Autoencoder for Periodic Material Generation

October 12, 2021 Tian Xie, Xiang Fu, Octavian-Eugen Ganea, Regina Barzilay, Tommi Jaakkola
application

Diffusion Normalizing Flow

October 14, 2021 Qinsheng Zhang, Yongxin Chen
application

Controllable and Compositional Generation with Latent-Space Energy-Based Models

October 21, 2021 Weili Nie, Arash Vahdat, Anima Anandkumar
methodology, performance

Likelihood Training of Schrodinger Bridge using Forward-Backward SDEs Theory

October 21, 2021 Tianrong Chen, Guan-Horng Liu, Evangelos A. Theodorou
methodology, theory

Zero-Shot Translation using Diffusion Models

November 02, 2021 Eliya Nachmani, Shaked Dovrat
methodology, performance

Realistic galaxy image simulation via score-based generative models

November 02, 2021 Michael J. Smith, James E. Geach, Ryan A. Jackson, Nikhil Arora, Connor Stone, Stéphane Courteau
application

Estimating High Order Gradients of the Data Distribution by Denoising

November 08, 2021 Chenlin Meng, Yang Song, Wenzhe Li, Stefano Ermon
performance

Palette: Image-to-Image Diffusion Models

November 10, 2021 Chitwan Saharia, William Chan, Huiwen Chang, Chris A. Lee, Jonathan Ho, Tim Salimans, David J. Fleet, Mohammad Norouzi
application

Simulating Diffusion Bridges with Score Matching

November 14, 2021 Valentin De Bortoli, Arnaud Doucet, Jeremy Heng, James Thornton
methodology, theory

Conditional Image Generation with Score-Based Diffusion Models

November 26, 2021 Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann
methodology

Blended Diffusion for Text-driven Editing of Natural Images

November 29, 2021 Omri Avrahami, Dani Lischinski, Ohad Fried
application

Vector Quantized Diffusion Model for Text-to-Image Synthesis

November 29, 2021 Shuyang Gu, Dong Chen, Jianmin Bao, Fang Wen, Bo Zhang, Dongdong Chen, Lu Yuan, Baining Guo
application

Diffusion Autoencoders: Toward a Meaningful and Decodable Representation

November 30, 2021 Konpat Preechakul, Nattanat Chatthee, Suttisak Wizadwongsa, Supasorn Suwajanakorn
methodology

SegDiff: Image Segmentation with Diffusion Probabilistic Models

December 01, 2021 Tomer Amit, Eliya Nachmani, Tal Shaharbany, Lior Wolf
application

Noise Distribution Adaptive Self-Supervised Image Denoising using Tweedie Distribution and Score-Matching

December 05, 2021 Kwanyoung Kim, Taesung Kwon, Jong Chul Ye
performance

Deblurring via Stochastic Refinement

December 05, 2021 Jay Whang, Mauricio Delbracio, Hossein Talebi, Chitwan Saharia, Alexandros G. Dimakis, Peyman Milanfar
methodology

A Conditional Point DIffusion-Refinement Paradigm for 3D Point Cloud Completion

December 07, 2021 Zhaoyang Lyu, Zhifeng Kong, Xudong Xu, Liang Pan, Dahua Lin
application

Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction

December 09, 2021 Hyungjin Chung, Byeongsu Sim, Jong Chul Ye
methodology

DiffuseMorph: Unsupervised Deformable Image Registration Along Continuous Trajectory Using Diffusion Models

December 09, 2021 Boah Kim, Inhwa Han, Jong Chul Ye
application

More Control for Free! Image Synthesis with Semantic Diffusion Guidance

December 10, 2021 Xihui Liu, Dong Huk Park, Samaneh Azadi, Gong Zhang, Arman Chopikyan, Yuxiao Hu, Humphrey Shi, Anna Rohrbach, Trevor Darrell
application

Step-unrolled Denoising Autoencoders for Text Generation

December 13, 2021 Nikolay Savinov, Junyoung Chung, Mikolaj Binkowski, Erich Elsen, Aaron van den Oord
methodology, application

Score-Based Generative Modeling with Critically-Damped Langevin Diffusion

December 14, 2021 Tim Dockhorn, Arash Vahdat, Karsten Kreis
methodology

Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

December 15, 2021 Zhisheng Xiao, Karsten Kreis, Arash Vahdat
methodology, performance

Heavy-tailed denoising score matching

December 17, 2021 Jacob Deasy, Nikola Simidjievski, Pietro Liò
methodology

GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

December 20, 2021 Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, Mark Chen
application

High-Resolution Image Synthesis with Latent Diffusion Models

December 20, 2021 Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, Björn Ommer
methodology

Ito-Taylor Sampling Scheme for Denoising Diffusion Probabilistic Models using Ideal Derivatives

December 26, 2021 Hideyuki Tachibana, Mocho Go, Muneyoshi Inahara, Yotaro Katayama, Yotaro Watanabe
theory, methodology

DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents

January 02, 2022 Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar
methodology

Probabilistic Mass Mapping with Neural Score Estimation

January 14, 2022 Benjamin Remy, Francois Lanusse, Niall Jeffrey, Jia Liu, Jean-Luc Starck, Ken Osato, Tim Schrabback
application

Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models

January 17, 2022 Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang
theory, methodology

RePaint: Inpainting using Denoising Diffusion Probabilistic Models

January 24, 2022 Andreas Lugmayr, Martin Danelljan, Andres Romero, Fisher Yu, Radu Timofte, Luc Van Gool
application, methodology

Unsupervised Denoising of Retinal OCT with Diffusion Probabilistic Model

January 27, 2022 Dewei Hu, Yuankai K. Tao, Ipek Oguz
application

Denoising Diffusion Restoration Models

January 27, 2022 Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song
methodology

DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs

January 28, 2022 Songxiang Liu, Dan Su, Dong Yu
methodology, application

From data to functa: Your data point is a function and you should treat it like one

January 28, 2022 Emilien Dupont, Hyunjik Kim, S. M. Ali Eslami, Danilo Rezende, Dan Rosenbaum
methodology

Progressive Distillation for Fast Sampling of Diffusion Models

February 01, 2022 Tim Salimans, Jonathan Ho
methodology

Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations

February 05, 2022 Jaehyeong Jo, Seul Lee, Sung Ju Hwang
application

Riemannian Score-Based Generative Modeling

February 06, 2022 Valentin De Bortoli, Emile Mathieu, Michael Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet
methodology, theory

InferGrad: Improving Diffusion Models for Vocoder by Considering Inference in Training

February 08, 2022 Zehua Chen, Xu Tan, Ke Wang, Shifeng Pan, Danilo Mandic, Lei He, Sheng Zhao
application

Diffusion bridges vector quantized Variational AutoEncoders

February 10, 2022 Max Cohen, Guillaume Quispe, Sylvain Le Corff, Charles Ollion, Eric Moulines
methodology, application

Conditional Diffusion Probabilistic Model for Speech Enhancement

February 10, 2022 Yen-Ju Lu, Zhong-Qiu Wang, Shinji Watanabe, Alexander Richard, Cheng Yu, Yu Tsao
application

Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality

February 11, 2022 Daniel Watson, William Chan, Jonathan Ho, Mohammad Norouzi
methodology

Understanding DDPM Latent Codes Through Optimal Transport

February 14, 2022 Valentin Khrulkov, Ivan Oseledets
theory

Truncated Diffusion Probabilistic Models

February 19, 2022 Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou
methodology

Pseudo Numerical Methods for Diffusion Models on Manifolds

February 20, 2022 Luping Liu, Yi Ren, Zhijie Lin, Zhou Zhao
methodology

Diffusion Causal Models for Counterfactual Estimation

February 21, 2022 Pedro Sanchez, Sotirios A. Tsaftaris
application

Conditional Simulation Using Diffusion Schrodinger Bridges

February 27, 2022 Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
methodology

Score-Based Generative Models for Molecule Generation

March 07, 2022 Dwaraknath Gnaneshwar, Bharath Ramsundar, Dhairya Gandhi, Rachel Kurchin, Venkatasubramanian Viswanathan
application

Towards performant and reliable undersampled MR reconstruction via diffusion model sampling

March 08, 2022 Cheng Peng, Pengfei Guo, S. Kevin Zhou, Vishal Patel, Rama Chellappa
application

Dynamic Dual-Output Diffusion Models

March 08, 2022 Yaniv Benny, Lior Wolf
methodology

Diffusion Models for Medical Anomaly Detection

March 08, 2022 Julia Wolleb, Florentin Bieder, Robin Sandkühler, Philippe C. Cattin
application

Score matching enables causal discovery of nonlinear additive noise models

March 08, 2022 Paul Rolland, Volkan Cevher, Matthäus Kleindessner, Chris Russel, Bernhard Schölkopf, Dominik Janzing, Francesco Locatello
methodology

Diffusion Probabilistic Modeling for Video Generation

March 16, 2022 Ruihan Yang, Prakhar Srivastava, Stephan Mandt
application

Dual Diffusion Implicit Bridges for Image-to-Image Translation

March 16, 2022 Xuan Su, Jiaming Song, Chenlin Meng, Stefano Ermon
methodology

MR Image Denoising and Super-Resolution Using Regularized Reverse Diffusion

March 23, 2022 Hyungjin Chung, Eun Sun Lee, Jong Chul Ye
application

Accelerating Bayesian Optimization for Biological Sequence design with Denoising Autoencoders

March 23, 2022 Samuel Stanton, Wesley Maddox, Nate Gruver, Phillip Maffettone, Emily Delaney, Peyton Greenside, Andrew Gordon Wilson
application

BBDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis

March 25, 2022 Max W. Y. Lam, Jun Wang, Dan Su, Dong Yu
methodology

Denoising Likelihood Score Matching for Conditional Score-based Data Generation

March 27, 2022 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
methodology

Diffusion Models for Counterfactual Explanations

March 29, 2022 Guillaume Jeanneret, Loïc Simon, Frédéric Jurie
application

SpecGrad: Diffusion Probabilistic Model based Neural Vocoder with Adaptive Noise Spectral Shaping

March 31, 2022 Yuma Koizumi, Heiga Zen, Kohei Yatabe, Nanxin Chen, Michiel Bacchiani
application

Equivariant Diffusion for Molecule Generation in 3D

March 31, 2022 Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling
methodology

Speech Enhancement with Score-Based Generative Models in the Complex STFT Domain

March 31, 2022 Simon Welker, Julius Richter, Timo Gerkmann
methodology

Generating High Fidelity Data from Low-density Regions using Diffusion Models

March 31, 2022 Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton Ferrer
methodology

Perception Prioritized Training of Diffusion Models

April 01, 2022 Jooyoung Choi, Jungbeom Lee, Chaehun Shin, Sungwon Kim, Hyunwoo Kim, Sungroh Yoon
methodology

KNN-Diffusion: Image Generation via Large-Scale Retrieval

April 06, 2022 Oron Ashual, Shelly Sheynin, Adam Polyak, Uriel Singer, Oran Gafni, Eliya Nachmani, Yaniv Taigman
application

Video Diffusion Models

April 07, 2022 Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, David J. Fleet
application

A Score-based Geometric Model for Molecular Dynamics Simulations

April 19, 2022 Fang Wu, Qiang Zhang, Xurui Jin, Yinghui Jiang, Stan Z. Li
application

FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech Synthesis

April 21, 2022 Rongjie Huang, Max W. Y. Lam, Jun Wang, Dan Su, Dong Yu, Yi Ren, Zhou Zhao
methodology

Retrieval-Augmented Diffusion Models

April 25, 2022 Andreas Blattmann, Robin Rombach, Kaan Oktay, Björn Ommer
application

Fast Sampling of Diffusion Models with Exponential Integrator

April 29, 2022 Qinsheng Zhang, Yongxin Chen
methodology

Subspace Diffusion Generative Models

May 03, 2022 Bowen Jing, Gabriele Corso, Renato Berlinghieri, Tommi Jaakkola
methodology

On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models

May 08, 2022 Vedant Singh, Surgan Jandial, Ayush Chopra, Siddharth Ramesh, Balaji Krishnamurthy, Vineeth N. Balasubramanian
application

Diffusion Models for Adversarial Purification

May 16, 2022 Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar
application