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Path Integral Sampler: a stochastic control approach for sampling

30 November 2021

Qinsheng Zhang

Yongxin Chen

DiffM

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Papers citing "Path Integral Sampler: a stochastic control approach for sampling"

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Title
Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities Tara Akhound-Sadegh Jungyoon Lee A. Bose Valentin De Bortoli Arnaud Doucet Michael M. Bronstein Dominique Beaini Siamak Ravanbakhsh Kirill Neklyudov Alexander Tong DiffM 17 0 0 19 Jun 2025
Rethinking Losses for Diffusion Bridge Samplers Sebastian Sanokowski Lukas Gruber Christoph Bartmann Sepp Hochreiter Sebastian Lehner DiffM 124 0 0 12 Jun 2025
Path Integral Optimiser: Global Optimisation via Neural Schrödinger-Föllmer Diffusion Max McGuinness Eirik Fladmark Francisco Vargas 18 0 0 07 Jun 2025
Progressive Tempering Sampler with Diffusion Severi Rissanen RuiKang OuYang Jiajun He Wenlin Chen Markus Heinonen Arno Solin José Miguel Hernández-Lobato DiffM 110 1 0 05 Jun 2025
Adaptive Destruction Processes for Diffusion Samplers Timofei Gritsaev Nikita Morozov Kirill Tamogashev D. Tiapkin S. Samsonov A. Naumov Dmitry Vetrov Nikolay Malkin 54 0 0 02 Jun 2025
Energy-based generator matching: A neural sampler for general state space Dongyeop Woo Minsu Kim Minkyu Kim Kiyoung Seong SungSoo Ahn 95 0 0 26 May 2025
Importance Weighted Score Matching for Diffusion Samplers with Enhanced Mode Coverage Chenguang Wang Xiaoyu Zhang Kaiyuan Cui Weichen Zhao Yongtao Guan Tianshu Yu DiffM 102 0 0 26 May 2025
On scalable and efficient training of diffusion samplers Minkyu Kim Kiyoung Seong Dongyeop Woo SungSoo Ahn Minsu Kim DiffM 143 0 0 26 May 2025
Energy-Based Coarse-Graining in Molecular Dynamics: A Flow-Based Framework Without Data Maximilian Stupp P. S. Koutsourelakis 85 0 0 29 Apr 2025
Improving the evaluation of samplers on multi-modal targets Louis Grenioux Maxence Noble Marylou Gabrié 454 0 0 11 Apr 2025
SpectR: Dynamically Composing LM Experts with Spectral Routing William Fleshman Benjamin Van Durme MoMe MoE 112 2 0 04 Apr 2025
Potential Score Matching: Debiasing Molecular Structure Sampling with Potential Energy Guidance Liya Guo Zun Wang Chang-Shu Liu Junlong Li Pipi Hu Yi Zhu DiffM 73 0 0 18 Mar 2025
Underdamped Diffusion Bridges with Applications to Sampling Denis Blessing Julius Berner Lorenz Richter Gerhard Neumann DiffM 138 6 0 02 Mar 2025
End-To-End Learning of Gaussian Mixture Priors for Diffusion Sampler Denis Blessing Xiaogang Jia Gerhard Neumann DiffM 100 1 0 01 Mar 2025
Value Gradient Sampler: Sampling as Sequential Decision Making Sangwoong Yoon Himchan Hwang Hyeokju Jeong Dong Kyu Shin Che-Sang Park Sehee Kwon Frank C. Park 141 0 0 18 Feb 2025
In-Context Parametric Inference: Point or Distribution Estimators? Sarthak Mittal Yoshua Bengio Nikolay Malkin Guillaume Lajoie 128 0 0 17 Feb 2025
Single-Step Consistent Diffusion Samplers Pascal Jutras-Dubé Patrick Pynadath Ruqi Zhang DiffM 166 0 0 17 Feb 2025
Neural Flow Samplers with Shortcut Models Wuhao Chen Zijing Ou Yingzhen Li 242 2 0 11 Feb 2025
Amortized In-Context Bayesian Posterior Estimation Sarthak Mittal Niels Leif Bracher Guillaume Lajoie P. Jaini Marcus A. Brubaker 114 2 0 10 Feb 2025
CAFuser: Condition-Aware Multimodal Fusion for Robust Semantic Perception of Driving Scenes Tim Broedermann Daniel Gehrig Yuqian Fu Luc Van Gool 133 31 0 28 Jan 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 157 8 0 10 Jan 2025
Sequential Controlled Langevin Diffusions Junhua Chen Lorenz Richter Julius Berner Denis Blessing Gerhard Neumann A. Anandkumar 140 22 0 10 Dec 2024
Denoising Fisher Training For Neural Implicit Samplers Weijian Luo Wei Deng 78 0 0 03 Nov 2024
Path Integral Control for Hybrid Dynamical Systems Hongzhe Yu Diana Frias Franco Aaron M. Johnson Yongxin Chen 65 0 0 01 Nov 2024
Learned Reference-based Diffusion Sampling for multi-modal distributions Maxence Noble Louis Grenioux Marylou Gabrié Alain Durmus DiffM 134 6 0 25 Oct 2024
Action abstractions for amortized sampling Oussama Boussif Léna Néhale Ezzine J. Viviano Michał Koziarski Moksh Jain Nikolay Malkin Emmanuel Bengio Rim Assouel Yoshua Bengio 96 0 0 19 Oct 2024
Training Neural Samplers with Reverse Diffusive KL Divergence Wenlin Chen Jiajun He Mingtian Zhang David Barber José Miguel Hernández-Lobato DiffM 134 8 0 16 Oct 2024
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series Byoungwoo Park Hyungi Lee Juho Lee AI4TS 211 1 0 08 Oct 2024
AutoLoRA: AutoGuidance Meets Low-Rank Adaptation for Diffusion Models Artur Kasymov Marcin Sendera Michał Stypułkowski Maciej Ziȩba Przemysław Spurek 142 1 0 04 Oct 2024
NETS: A Non-Equilibrium Transport Sampler M. S. Albergo Eric Vanden-Eijnden DiffM 136 22 0 03 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 483 7 0 02 Oct 2024
BNEM: A Boltzmann Sampler Based on Bootstrapped Noised Energy Matching RuiKang OuYang Bo Qiang José Miguel Hernández-Lobato 151 0 0 15 Sep 2024
Neural Entropy Akhil Premkumar DiffM 201 1 0 05 Sep 2024
Iterated Energy-based Flow Matching for Sampling from Boltzmann Densities Dongyeop Woo SungSoo Ahn 81 8 0 29 Aug 2024
Flexible Bayesian Last Layer Models Using Implicit Priors and Diffusion Posterior Sampling Jian Xu Zhiqi Lin Shigui Li Min Chen Junmei Yang Delu Zeng John Paisley BDL 61 0 0 07 Aug 2024
Importance Corrected Neural JKO Sampling Johannes Hertrich Robert Gruhlke 102 2 0 29 Jul 2024
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference Jian Xu Delu Zeng John Paisley DiffM 85 1 0 24 Jul 2024
Understanding Reinforcement Learning-Based Fine-Tuning of Diffusion Models: A Tutorial and Review Masatoshi Uehara Yulai Zhao Tommaso Biancalani Sergey Levine 144 32 0 18 Jul 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
Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models Sangwoong Yoon Himchan Hwang Dohyun Kwon Yung-Kyun Noh Frank C. Park 85 3 0 30 Jun 2024
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling Denis Blessing Xiaogang Jia Johannes Esslinger Francisco Vargas Gerhard Neumann 135 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
Stochastic Optimal Control for Diffusion Bridges in Function Spaces Byoungwoo Park Jungwon Choi Sungbin Lim Juho Lee 136 4 0 31 May 2024
Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models Masatoshi Uehara Yulai Zhao Ehsan Hajiramezanali Gabriele Scalia Gökçen Eraslan Avantika Lal Sergey Levine Tommaso Biancalani 133 16 0 30 May 2024
Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows A. Cabezas Louis Sharrock Christopher Nemeth 71 4 0 23 May 2024
Control, Transport and Sampling: Towards Better Loss Design Qijia Jiang David Nabergoj OT 68 0 0 22 May 2024
One-step data-driven generative model via Schrödinger Bridge Hanwen Huang DiffM 80 4 0 21 May 2024
Liouville Flow Importance Sampler Yifeng Tian Nishant Panda Yen Ting Lin 121 13 0 03 May 2024
Physics-Informed Diffusion Models Jan-Hendrik Bastek WaiChing Sun D. Kochmann DiffM AI4CE 192 20 0 21 Mar 2024
Probabilistic Forecasting with Stochastic Interpolants and Föllmer Processes Yifan Chen Mark Goldstein Mengjian Hua M. S. Albergo Nicholas M. Boffi Eric Vanden-Eijnden AI4TS 110 19 0 20 Mar 2024