From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training

10 January 2025

Papers citing "From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training"

50 / 54 papers shown

Title
RNE: a plug-and-play framework for diffusion density estimation and inference-time control Jiajun He Jose Miguel Hernandez-Lobato Yuanqi Du Francisco Vargas 100 0 0 06 Jun 2025
Adaptive Destruction Processes for Diffusion Samplers Timofei Gritsaev Nikita Morozov Kirill Tamogashev D. Tiapkin S. Samsonov A. Naumov Dmitry Vetrov Nikolay Malkin 60 0 0 02 Jun 2025
On scalable and efficient training of diffusion samplers Minkyu Kim Kiyoung Seong Dongyeop Woo SungSoo Ahn Minsu Kim DiffM 150 0 0 26 May 2025
Energy-based generator matching: A neural sampler for general state space Dongyeop Woo Minsu Kim Minkyu Kim Kiyoung Seong SungSoo Ahn 97 0 0 26 May 2025
MetaGFN: Exploring Distant Modes with Adapted Metadynamics for Continuous GFlowNets Dominic Phillips F. Cipcigan 107 4 0 28 Aug 2024
Dynamical Measure Transport and Neural PDE Solvers for Sampling Jingtong Sun Julius Berner Lorenz Richter Marius Zeinhofer Johannes Müller Kamyar Azizzadenesheli Anima Anandkumar OT DiffM 89 11 0 10 Jul 2024
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling Denis Blessing Xiaogang Jia Johannes Esslinger Francisco Vargas Gerhard Neumann 146 27 0 11 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 191 32 0 31 May 2024
Discrete Probabilistic Inference as Control in Multi-path Environments T. Deleu Padideh Nouri Nikolay Malkin Doina Precup Yoshua Bengio 183 31 0 15 Feb 2024
Particle Denoising Diffusion Sampler Angus Phillips Hai-Dang Dau M. Hutchinson Valentin De Bortoli George Deligiannidis Arnaud Doucet DiffM 135 30 0 09 Feb 2024
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities Tara Akhound-Sadegh Jarrid Rector-Brooks A. Bose Sarthak Mittal Pablo Lemos ... Siamak Ravanbakhsh Gauthier Gidel Yoshua Bengio Nikolay Malkin Alexander Tong DiffM 112 58 0 09 Feb 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 239 28 0 07 Feb 2024
Improving Gradient-guided Nested Sampling for Posterior Inference Pablo Lemos Nikolay Malkin Will Handley Yoshua Bengio Y. Hezaveh Laurence Perreault Levasseur BDL 109 11 0 06 Dec 2023
Bespoke Solvers for Generative Flow Models Neta Shaul Juan C. Pérez Ricky T. Q. Chen Ali K. Thabet Albert Pumarola Y. Lipman 81 27 0 29 Oct 2023
Generative Fractional Diffusion Models Gabriel Nobis Maximilian Springenberg Marco Aversa Michael Detzel Rembert Daems ... Tolga Birdal Manfred Opper Christoph Knochenhauer Luis Oala Wojciech Samek DiffM 76 6 0 26 Oct 2023
Towards equilibrium molecular conformation generation with GFlowNets Alexandra Volokhova Michal Koziarski Alex Hernández-García Cheng-Hao Liu Santiago Miret Pablo Lemos Luca Thiede Zichao Yan Alán Aspuru-Guzik Yoshua Bengio 75 11 0 20 Oct 2023
Variational Inference for SDEs Driven by Fractional Noise Rembert Daems Manfred Opper Guillaume Crevecoeur Tolga Birdal 99 6 0 19 Oct 2023
Efficient Integrators for Diffusion Generative Models Kushagra Pandey Maja R. Rudolph Stephan Mandt DiffM 68 11 0 11 Oct 2023
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization Dinghuai Zhang Ricky Tian Qi Chen Cheng-Hao Liu Aaron C. Courville Yoshua Bengio 125 49 0 04 Oct 2023
Generative Flow Networks: a Markov Chain Perspective T. Deleu Yoshua Bengio BDL 92 9 0 04 Jul 2023
Improved sampling via learned diffusions Lorenz Richter Julius Berner DiffM 121 65 0 03 Jul 2023
Denoising Diffusion Samplers Francisco Vargas Will Grathwohl Arnaud Doucet DiffM 86 91 0 27 Feb 2023
Better Training of GFlowNets with Local Credit and Incomplete Trajectories L. Pan Nikolay Malkin Dinghuai Zhang Yoshua Bengio 108 72 0 03 Feb 2023
A theory of continuous generative flow networks Salem Lahlou T. Deleu Pablo Lemos Dinghuai Zhang Alexandra Volokhova Alex Hernández-García Léna Néhale Ezzine Yoshua Bengio Nikolay Malkin AI4CE 146 93 0 30 Jan 2023
Learning Interpolations between Boltzmann Densities Bálint Máté Franccois Fleuret 137 29 0 18 Jan 2023
An optimal control perspective on diffusion-based generative modeling Julius Berner Lorenz Richter Karen Ullrich DiffM 154 97 0 02 Nov 2022
GFlowNets and variational inference Nikolay Malkin Salem Lahlou T. Deleu Xu Ji J. E. Hu Katie Everett Dinghuai Zhang Yoshua Bengio BDL 231 89 0 02 Oct 2022
Learning GFlowNets from partial episodes for improved convergence and stability Kanika Madan Jarrid Rector-Brooks Maksym Korablyov Emmanuel Bengio Moksh Jain A. Nica Tom Bosc Yoshua Bengio Nikolay Malkin 100 102 0 26 Sep 2022
Score-Based Diffusion meets Annealed Importance Sampling Arnaud Doucet Will Grathwohl A. G. Matthews Heiko Strathmann DiffM 117 46 0 16 Aug 2022
Flow Annealed Importance Sampling Bootstrap Laurence Illing Midgley Vincent Stimper G. Simm Bernhard Schölkopf José Miguel Hernández-Lobato 136 95 0 03 Aug 2022
Fast Sampling of Diffusion Models with Exponential Integrator Qinsheng Zhang Yongxin Chen DiffM 114 439 0 29 Apr 2022
Trajectory balance: Improved credit assignment in GFlowNets Nikolay Malkin Moksh Jain Emmanuel Bengio Chen Sun Yoshua Bengio 272 186 0 31 Jan 2022
Continual Repeated Annealed Flow Transport Monte Carlo A. G. Matthews Michael Arbel Danilo Jimenez Rezende Arnaud Doucet OT 121 53 0 31 Jan 2022
High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach A. Blattmann Dominik Lorenz Patrick Esser Bjorn Ommer 3DV 615 15,855 0 20 Dec 2021
Interpolating between BSDEs and PINNs: deep learning for elliptic and parabolic boundary value problems Nikolas Nusken Lorenz Richter PINN DiffM 103 30 0 07 Dec 2021
Path Integral Sampler: a stochastic control approach for sampling Qinsheng Zhang Yongxin Chen DiffM 119 119 0 30 Nov 2021
Generalized Normalizing Flows via Markov Chains Paul Hagemann J. Hertrich Gabriele Steidl BDL DiffM AI4CE 103 25 0 24 Nov 2021
GFlowNet Foundations Yoshua Bengio Salem Lahlou T. Deleu J. E. Hu Mo Tiwari Emmanuel Bengio 111 240 0 17 Nov 2021
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation Emmanuel Bengio Moksh Jain Maksym Korablyov Doina Precup Yoshua Bengio 105 338 0 08 Jun 2021
Efficient and Accurate Gradients for Neural SDEs Patrick Kidger James Foster Xuechen Li Terry Lyons DiffM 113 66 0 27 May 2021
Diffusion Models Beat GANs on Image Synthesis Prafulla Dhariwal Alex Nichol 410 8,010 0 11 May 2021
Annealed Flow Transport Monte Carlo Michael Arbel A. G. Matthews Arnaud Doucet 95 78 0 15 Feb 2021
Nested Sampling Methods J. Buchner 121 63 0 24 Jan 2021
Maximum Likelihood Training of Score-Based Diffusion Models Yang Song Conor Durkan Iain Murray Stefano Ermon DiffM 230 676 0 22 Jan 2021
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 562 6,606 0 26 Nov 2020
VarGrad: A Low-Variance Gradient Estimator for Variational Inference Lorenz Richter Ayman Boustati Nikolas Nusken Francisco J. R. Ruiz Ömer Deniz Akyildiz DRL 231 54 0 20 Oct 2020
An invitation to sequential Monte Carlo samplers Chenguang Dai J. Heng Pierre E. Jacob N. Whiteley 134 68 0 23 Jul 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 1.0K 18,532 0 19 Jun 2020
Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space Nikolas Nusken Lorenz Richter AI4CE 95 112 0 11 May 2020
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 219 1,724 0 05 Dec 2019