Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization

4 October 2023

Papers citing "Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization"

21 / 21 papers shown

Title
Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching Aaron J. Havens Benjamin Kurt Miller Bing Yan Carles Domingo-Enrich Anuroop Sriram ... Brandon Amos Brian Karrer Xiang Fu Guan-Horng Liu Ricky T. Q. Chen DiffM 50 0 0 16 Apr 2025
Single-Step Consistent Diffusion Samplers Pascal Jutras-Dubé Patrick Pynadath Ruqi Zhang DiffM 75 0 0 17 Feb 2025
From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training Julius Berner Lorenz Richter Marcin Sendera Jarrid Rector-Brooks Nikolay Malkin OffRL 60 3 0 10 Jan 2025
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Zhen Liu Tim Z. Xiao Weiyang Liu Yoshua Bengio Dinghuai Zhang 123 2 0 10 Dec 2024
Training Neural Samplers with Reverse Diffusive KL Divergence Jiajun He Wenlin Chen Mingtian Zhang David Barber José Miguel Hernández-Lobato DiffM 37 4 0 16 Oct 2024
Adaptive teachers for amortized samplers Minsu Kim Sanghyeok Choi Taeyoung Yun Emmanuel Bengio Leo Feng Jarrid Rector-Brooks Sungsoo Ahn Jinkyoo Park Nikolay Malkin Yoshua Bengio 137 2 0 02 Oct 2024
Baking Symmetry into GFlowNets George Ma Emmanuel Bengio Yoshua Bengio Dinghuai Zhang 45 8 0 08 Jun 2024
Amortizing intractable inference in diffusion models for vision, language, and control S. Venkatraman Moksh Jain Luca Scimeca Minsu Kim Marcin Sendera ... Alexandre Adam Jarrid Rector-Brooks Yoshua Bengio Glen Berseth Nikolay Malkin 68 24 0 31 May 2024
Improved off-policy training of diffusion samplers Marcin Sendera Minsu Kim Sarthak Mittal Pablo Lemos Luca Scimeca Jarrid Rector-Brooks Alexandre Adam Yoshua Bengio Nikolay Malkin OffRL 66 17 0 07 Feb 2024
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors Wasu Top Piriyakulkij Yingheng Wang Volodymyr Kuleshov DiffM 32 1 0 05 Jan 2024
SE(3) Equivariant Augmented Coupling Flows Laurence I. Midgley Vincent Stimper Javier Antorán Emile Mathieu Bernhard Schölkopf José Miguel Hernández-Lobato 30 22 0 20 Aug 2023
Improved sampling via learned diffusions Lorenz Richter Julius Berner DiffM 26 52 0 03 Jul 2023
To smooth a cloud or to pin it down: Guarantees and Insights on Score Matching in Denoising Diffusion Models Francisco Vargas Teodora Reu A. Kerekes Michael M Bronstein DiffM 35 1 0 16 May 2023
DAG Matters! GFlowNets Enhanced Explainer For Graph Neural Networks Wenqian Li Yinchuan Li Zhigang Li Jianye Hao Yan Pang 83 29 0 04 Mar 2023
CFlowNets: Continuous Control with Generative Flow Networks Yinchuan Li Shuang Luo Haozhi Wang Jianye Hao 83 20 0 04 Mar 2023
Distributional GFlowNets with Quantile Flows Dinghuai Zhang L. Pan Ricky T. Q. Chen Aaron Courville Yoshua Bengio 29 25 0 11 Feb 2023
Generative Augmented Flow Networks L. Pan Dinghuai Zhang Aaron Courville Longbo Huang Yoshua Bengio 104 42 0 07 Oct 2022
GFlowNets and variational inference Nikolay Malkin Salem Lahlou T. Deleu Xu Ji J. E. Hu Katie Everett Dinghuai Zhang Yoshua Bengio BDL 134 77 0 02 Oct 2022
Convergence of score-based generative modeling for general data distributions Holden Lee Jianfeng Lu Yixin Tan DiffM 189 128 0 26 Sep 2022
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions Sitan Chen Sinho Chewi Jungshian Li Yuanzhi Li Adil Salim Anru R. Zhang DiffM 132 246 0 22 Sep 2022
Unifying Likelihood-free Inference with Black-box Optimization and Beyond Dinghuai Zhang Jie Fu Yoshua Bengio Aaron Courville 29 13 0 06 Oct 2021