Path Integral Sampler: a stochastic control approach for sampling

30 November 2021

Qinsheng Zhang

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

50 / 76 papers shown

Title
Energy-Based Coarse-Graining in Molecular Dynamics: A Flow-Based Framework Without Data Maximilian Stupp P. S. Koutsourelakis 40 0 0 29 Apr 2025
Improving the evaluation of samplers on multi-modal targets Louis Grenioux Maxence Noble Marylou Gabrié 116 0 0 11 Apr 2025
SpectR: Dynamically Composing LM Experts with Spectral Routing William Fleshman Benjamin Van Durme MoMe MoE 60 0 0 04 Apr 2025
Potential Score Matching: Debiasing Molecular Structure Sampling with Potential Energy Guidance Liya Guo Zun Wang Chang-Shu Liu Jiashi Li Pipi Hu Yi Zhu DiffM 45 0 0 18 Mar 2025
Underdamped Diffusion Bridges with Applications to Sampling Denis Blessing Julius Berner Lorenz Richter Gerhard Neumann DiffM 39 1 0 02 Mar 2025
End-To-End Learning of Gaussian Mixture Priors for Diffusion Sampler Denis Blessing Xiaogang Jia Gerhard Neumann DiffM 48 0 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 74 0 0 18 Feb 2025
In-Context Parametric Inference: Point or Distribution Estimators? Sarthak Mittal Yoshua Bengio Nikolay Malkin Guillaume Lajoie 72 0 0 17 Feb 2025
Single-Step Consistent Diffusion Samplers Pascal Jutras-Dubé Patrick Pynadath Ruqi Zhang DiffM 78 0 0 17 Feb 2025
Neural Flow Samplers with Shortcut Models Wuhao Chen Zijing Ou Yingzhen Li 85 0 0 11 Feb 2025
Amortized In-Context Bayesian Posterior Estimation Sarthak Mittal Niels Leif Bracher Guillaume Lajoie P. Jaini Marcus A. Brubaker 62 1 0 10 Feb 2025
CAFuser: Condition-Aware Multimodal Fusion for Robust Semantic Perception of Driving Scenes Tim Broedermann Christos Sakaridis Yuqian Fu Luc Van Gool 62 5 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 60 3 0 10 Jan 2025
Denoising Fisher Training For Neural Implicit Samplers Weijian Luo Wei Deng 36 0 0 03 Nov 2024
Path Integral Control for Hybrid Dynamical Systems Hongzhe Yu Diana Frias Franco Aaron M. Johnson Yongxin Chen 28 0 0 01 Nov 2024
Learned Reference-based Diffusion Sampling for multi-modal distributions Maxence Noble Louis Grenioux Marylou Gabrié Alain Durmus DiffM 31 2 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 28 0 0 19 Oct 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
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series Byoungwoo Park Hyungi Lee Juho Lee AI4TS 41 0 0 08 Oct 2024
An Efficient On-Policy Deep Learning Framework for Stochastic Optimal Control Mengjian Hua Matthieu Laurière Eric Vanden-Eijnden 31 3 0 07 Oct 2024
AutoLoRA: AutoGuidance Meets Low-Rank Adaptation for Diffusion Models Artur Kasymov Marcin Sendera Michał Stypułkowski Maciej Ziȩba P. Spurek 33 1 0 04 Oct 2024
NETS: A Non-Equilibrium Transport Sampler M. S. Albergo Eric Vanden-Eijnden DiffM 47 9 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 159 2 0 02 Oct 2024
BNEM: A Boltzmann Sampler Based on Bootstrapped Noised Energy Matching RuiKang OuYang Bo Qiang José Miguel Hernández-Lobato 88 0 0 15 Sep 2024
Neural Entropy Akhil Premkumar DiffM 26 0 0 05 Sep 2024
Iterated Energy-based Flow Matching for Sampling from Boltzmann Densities Dongyeop Woo Sungsoo Ahn 32 5 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 28 0 0 07 Aug 2024
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference Jian Xu Delu Zeng John Paisley DiffM 31 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 63 22 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 39 8 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 34 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 50 16 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 68 24 0 31 May 2024
Stochastic Optimal Control for Diffusion Bridges in Function Spaces Byoungwoo Park Jungwon Choi Sungbin Lim Juho Lee 50 3 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 50 13 0 30 May 2024
Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows A. Cabezas Louis Sharrock Christopher Nemeth 34 1 0 23 May 2024
Control, Transport and Sampling: Towards Better Loss Design Qijia Jiang David Nabergoj OT 38 0 0 22 May 2024
One-step data-driven generative model via Schrödinger Bridge Hanwen Huang DiffM 31 4 0 21 May 2024
Liouville Flow Importance Sampler Yifeng Tian Nishant Panda Yen Ting Lin 36 8 0 03 May 2024
Physics-Informed Diffusion Models Jan-Hendrik Bastek WaiChing Sun D. Kochmann DiffM AI4CE 47 11 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 33 16 0 20 Mar 2024
Soft-constrained Schrodinger Bridge: a Stochastic Control Approach Jhanvi Garg Xianyang Zhang Quan Zhou DiffM OT 40 0 0 04 Mar 2024
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion Ye He Kevin Rojas Molei Tao DiffM 38 8 0 27 Feb 2024
Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control Masatoshi Uehara Yulai Zhao Kevin Black Ehsan Hajiramezanali Gabriele Scalia N. Diamant Alex Tseng Tommaso Biancalani Sergey Levine 42 42 0 23 Feb 2024
Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion Yujia Huang Adishree S. Ghatare Yuanzhe Liu Ziniu Hu Qinsheng Zhang Chandramouli Shama Sastry Francesco Ferroni Sageev Oore Yisong Yue DiffM 55 21 0 22 Feb 2024
Stochastic Localization via Iterative Posterior Sampling Louis Grenioux Maxence Noble Marylou Gabrié Alain Durmus DiffM 43 12 0 16 Feb 2024
Target Score Matching Valentin De Bortoli M. Hutchinson Peter Wirnsberger Arnaud Doucet DiffM 35 17 0 13 Feb 2024
Particle Denoising Diffusion Sampler Angus Phillips Hai-Dang Dau M. Hutchinson Valentin De Bortoli George Deligiannidis Arnaud Doucet DiffM 62 25 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 37 41 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 66 17 0 07 Feb 2024