1. Accelerating Score-based Generative Models for High-Resolution Image Synthesis
    Hengyuan Ma, Li Zhang, Xiatian Zhu, Jingfeng Zhang, Jianfeng Feng
    arXiv 2022. Paper  
    2022-06-08
    2022-06-08
  2. Diffusion-GAN: Training GANs with Diffusion
    Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou
    arXiv 2022. Paper  
    2022-06-05
    2022-06-05
  3. 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  
    2022-06-02
    2022-06-02
  4. Elucidating the Design Space of Diffusion-Based Generative Models
    Tero Karras, Miika Aittala, Timo Aila, Samuli Laine
    arXiv 2022. Paper  
    2022-06-01
    2022-06-01
  5. On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models
    Kamil Deja, Anna Kuzina, Tomasz Trzciński, Jakub M. Tomczak
    arXiv 2022. Paper  
    2022-05-31
    2022-05-31
  6. A Continuous Time Framework for Discrete Denoising Models
    Andrew Campbell, Joe Benton, Valentin De Bortoli, Tom Rainforth, George Deligiannidis, Arnaud Doucet
    arXiv 2022. Paper  
    2022-05-30
    2022-05-30
  7. Few-Shot Diffusion Models
    Giorgio Giannone, Didrik Nielsen, Ole Winther
    arXiv 2022. Paper  
    2022-05-30
    2022-05-30
  8. 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  
    2022-05-27
    2022-05-27
  9. Accelerating Diffusion Models via Early Stop of the Diffusion Process
    Zhaoyang Lyu, Xudong XU, Ceyuan Yang, Dahua Lin, Bo Dai
    ICML 2022. Paper  
    2022-05-25
    2022-05-25
  10. 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  
    2022-05-08
    2022-05-08
  11. Subspace Diffusion Generative Models
    Bowen Jing, Gabriele Corso, Renato Berlinghieri, Tommi Jaakkola
    arXiv 2022. Paper   Github  
    2022-05-03
    2022-05-03
  12. Fast Sampling of Diffusion Models with Exponential Integrator
    Qinsheng Zhang, Yongxin Chen
    arXiv 2022. Paper  
    2022-04-29
    2022-04-29
  13. Retrieval-Augmented Diffusion Models
    Andreas Blattmann1, Robin Rombach1, Kaan Oktay, Björn Ommer
    arXiv 2022. Paper  
    2022-04-25
    2022-04-25
  14. Perception Prioritized Training of Diffusion Models
    Jooyoung Choi, Jungbeom Lee, Chaehun Shin, Sungwon Kim, Hyunwoo Kim, Sungroh Yoon
    arXiv 2022. Paper   Github  
    2022-04-01
    2022-04-01
  15. 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  
    2022-03-31
    2022-03-31
  16. Diffusion Models for Counterfactual Explanations
    Guillaume Jeanneret, Loïc Simon, Frédéric Jurie
    arXiv 2022. Paper  
    2022-03-29
    2022-03-29
  17. 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  
    2022-03-27
    2022-03-27
  18. Dynamic Dual-Output Diffusion Models
    Yaniv Benny, Lior Wolf
    arXiv 2022. Paper  
    2022-03-08
    2022-03-08
  19. Conditional Simulation Using Diffusion Schrödinger Bridges
    Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
    arXiv 2022. Paper  
    2022-02-27
    2022-02-27
  20. Diffusion Causal Models for Counterfactual Estimation
    Pedro Sanchez, Sotirios A. Tsaftaris
    PMLR 2022. Paper  
    2022-02-21
    2022-02-21
  21. Pseudo Numerical Methods for Diffusion Models on Manifolds
    Luping Liu, Yi Ren, Zhijie Lin, Zhou Zhao
    ICLR 2022. Paper   Github  
    2022-02-20
    2022-02-20
  22. Truncated Diffusion Probabilistic Models
    Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou
    arXiv 2022. Paper  
    2022-02-19
    2022-02-19
  23. Understanding DDPM Latent Codes Through Optimal Transport
    Valentin Khrulkov, Ivan Oseledets
    arXiv 2022. Paper  
    2022-02-14
    2022-02-14
  24. Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality
    Daniel Watson, William Chan, Jonathan Ho, Mohammad Norouzi
    ICLR 2022. Paper  
    2022-02-11
    2022-02-11
  25. Progressive Distillation for Fast Sampling of Diffusion Models
    Tim Salimans, Jonathan Ho
    ICLR 2022. Paper  
    2022-02-01
    2022-02-01
  26. 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  
    2022-01-17
    2022-01-17
  27. DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents
    Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar
    arXiv 2022. Paper   Github  
    2022-01-02
    2022-01-02
  28. Diffusion Autoencoders: Toward a Meaningful and Decodable Representation
    Konpat Preechakul, Nattanat Chatthee, Suttisak Wizadwongsa, Supasorn Suwajanakorn
    arXiv 2021. Paper   Project  
    2021-12-30
    2021-12-30
  29. 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  
    2021-12-26
    2021-12-26
  30. High-Resolution Image Synthesis with Latent Diffusion Models
    Robin Rombach1, Andreas Blattmann1, Dominik Lorenz, Patrick Esser, Björn Ommer
    arXiv 2021. Paper   Github  
    2021-12-20
    2021-12-20
  31. 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  
    2021-12-20
    2021-12-20
  32. Heavy-tailed denoising score matching
    Jacob Deasy, Nikola Simidjievski, Pietro Liò
    arXiv 2021. Paper  
    2021-12-17
    2021-12-17
  33. High Fidelity Visualization of What Your Self-Supervised Representation Knows About
    Florian Bordes, Randall Balestriero, Pascal Vincent
    arXiv 2021. Paper  
    2021-12-16
    2021-12-16
  34. Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
    Zhisheng Xiao, Karsten Kreis, Arash Vahdat
    arXiv 2021. Paper   Project  
    2021-12-15
    2021-12-15
  35. Score-Based Generative Modeling with Critically-Damped Langevin Diffusion
    Tim Dockhorn, Arash Vahdat, Karsten Kreis
    arXiv 2021. Paper   Project  
    2021-12-14
    2021-12-14
  36. 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  
    2021-12-10
    2021-12-10
  37. 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  
    2021-12-03
    2021-12-03
  38. Conditional Image Generation with Score-Based Diffusion Models
    Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann
    arXiv 2021. Paper  
    2021-11-26
    2021-11-26
  39. 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  
    2021-11-24
    2021-11-24
  40. Diffusion Normalizing Flow
    Qinsheng Zhang, Yongxin Chen
    NeurIPS 2021. Paper   Github  
    2021-10-14
    2021-10-14
  41. Denoising Diffusion Gamma Models
    Eliya Nachmani1, Robin San Roman1, Lior Wolf
    arXiv 2021. Paper  
    2021-10-10
    2021-10-10
  42. Score-based Generative Neural Networks for Large-Scale Optimal Transport
    Max Daniels, Tyler Maunu, Paul Hand
    arXiv 2021. Paper  
    2021-10-07
    2021-10-07
  43. Score-Based Generative Classifiers
    Roland S. Zimmermann, Lukas Schott, Yang Song, Benjamin A. Dunn, David A. Klindt
    arXiv 2021. Paper  
    2021-10-01
    2021-10-01
  44. Bilateral Denoising Diffusion Models
    Max W. Y. Lam, Jun Wang, Rongjie Huang, Dan Su, Dong Yu
    arXiv 2021. Paper   Project  
    2021-08-26
    2021-08-26
  45. ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis
    Patrick Esser1, Robin Rombach1, Andreas Blattmann1, Björn Ommer
    NeurIPS 2021. Paper   Project  
    2021-08-19
    2021-08-19
  46. ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models
    Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, Sungroh Yoon
    ICCV 2021 (Oral). Paper   Github  
    2021-08-06
    2021-08-06
  47. 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  
    2021-08-02
    2021-08-02
  48. Structured Denoising Diffusion Models in Discrete State-Spaces
    Jacob Austin1, Daniel D. Johnson1, Jonathan Ho, Daniel Tarlow, Rianne van den Berg
    arXiv 2021. Paper  
    2021-07-07
    2021-07-07
  49. Variational Diffusion Models
    Diederik P. Kingma1, Tim Salimans1, Ben Poole, Jonathan Ho
    arXiv 2021. Paper   Github  
    2021-07-01
    2021-07-01
  50. Deep Generative Learning via Schrödinger Bridge
    Gefei Wang, Yuling Jiao, Qian Xu, Yang Wang, Can Yang
    ICML 2021. Paper  
    2021-06-19
    2021-06-19
  51. Non Gaussian Denoising Diffusion Models
    Eliya Nachmani1, Robin San Roman1, Lior Wolf
    arXiv 2021. Paper   Project  
    2021-06-14
    2021-06-14
  52. D2C: Diffusion-Denoising Models for Few-shot Conditional Generation
    Abhishek Sinha1, Jiaming Song1, Chenlin Meng, Stefano Ermon
    arXiv 2021. Paper   Project   Github  
    2021-06-12
    2021-06-12
  53. Score-based Generative Modeling in Latent Space
    Arash Vahdat1, Karsten Kreis1, Jan Kautz
    arXiv 2021. Paper  
    2021-06-10
    2021-06-10
  54. Learning to Efficiently Sample from Diffusion Probabilistic Models
    Daniel Watson, Jonathan Ho, Mohammad Norouzi, William Chan
    arXiv 2021. Paper  
    2021-06-07
    2021-06-07
  55. A Variational Perspective on Diffusion-Based Generative Models and Score Matching
    Chin-Wei Huang, Jae Hyun Lim, Aaron Courville
    ICML Workshop 2021. Paper   Github  
    2021-06-05
    2021-06-05
  56. Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling
    Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet
    arXiv 2021. Paper   Project   Github  
    2021-06-01
    2021-06-01
  57. On Fast Sampling of Diffusion Probabilistic Models
    Zhifeng Kong, Wei Ping
    ICML Workshop 2021. Paper   Github  
    2021-05-31
    2021-05-31
  58. 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  
    2021-05-30
    2021-05-30
  59. 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  
    2021-05-28
    2021-05-28
  60. Diffusion Models Beat GANs on Image Synthesis
    Prafulla Dhariwal1, Alex Nichol1
    arXiv 2021. Paper   Github  
    2021-05-11
    2021-05-11
  61. Image Super-Resolution via Iterative Refinement
    Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi
    arXiv 2021. Paper   Project   Github  
    2021-04-15
    2021-04-15
  62. Noise Estimation for Generative Diffusion Models
    Robin San-Roman1, Eliya Nachmani1, Lior Wolf
    arXiv 2021. Paper  
    2021-04-06
    2021-04-06
  63. Improved Denoising Diffusion Probabilistic Models
    Alex Nichol1, Prafulla Dhariwal1
    ICLR 2021. Paper   Github  
    2021-02-18
    2021-02-18
  64. Maximum Likelihood Training of Score-Based Diffusion Models
    Yang Song1, Conor Durkan1, Iain Murray, Stefano Ermon
    arXiv 2021. Paper  
    2021-01-22
    2021-01-22
  65. Learning Energy-Based Models by Diffusion Recovery Likelihood
    Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma
    ICLR 2021. Paper   Github  
    2020-12-15
    2020-12-15
  66. 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  
    2020-11-26
    2020-11-26
  67. 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  
    2020-10-16
    2020-10-16
  68. Denoising Diffusion Implicit Models*
    Jiaming Song, Chenlin Meng, Stefano Ermon
    ICLR 2021. Paper   Github  
    2020-10-06
    2020-10-06
  69. 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  
    2020-09-11
    2020-09-11
  70. Denoising Diffusion Probabilistic Models
    Jonathan Ho, Ajay Jain, Pieter Abbeel
    NeurIPS 2020. Paper   Github   Github2  
    2020-06-19
    2020-06-19
  71. Improved Techniques for Training Score-Based Generative Models
    Yang Song, Stefano Ermon
    NeurIPS 2020. Paper   Github  
    2020-06-16
    2020-06-16
  72. Generative Modeling by Estimating Gradients of the Data Distribution
    Yang Song, Stefano Ermon
    NeurIPS 2019. Paper   Project   Github  
    2019-07-12
    2019-07-12
  73. Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit
    Belinda Tzen, Maxim Raginsky
    arXiv 2019. Paper  
    2019-05-23
    2019-05-23
  74. Deep Unsupervised Learning using Nonequilibrium Thermodynamics
    Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, Surya Ganguli
    ICML 2015. Paper   Github  
    2015-03-02
    2015-03-02
Counts - 74   Back to top