An optimal control perspective on diffusion-based generative modeling

2 November 2022

Papers citing "An optimal control perspective on diffusion-based generative modeling"

50 / 66 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
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
Improving the evaluation of samplers on multi-modal targets Louis Grenioux Maxence Noble Marylou Gabrié 107 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
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 43 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 69 0 0 18 Feb 2025
Single-Step Consistent Diffusion Samplers Pascal Jutras-Dubé Patrick Pynadath Ruqi Zhang DiffM 75 0 0 17 Feb 2025
Neural Flow Samplers with Shortcut Models Wuhao Chen Zijing Ou Yingzhen Li 85 0 0 11 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
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models Daniela de Albuquerque John Pearson DiffM 59 0 0 03 Jan 2025
Solving Inverse Problems via Diffusion Optimal Control Henry Li Marcus Pereira 71 0 0 21 Dec 2024
Sampling from Boltzmann densities with physics informed low-rank formats Paul Hagemann Janina Enrica Schutte David Sommer Martin Eigel Gabriele Steidl 73 0 0 10 Dec 2024
Streaming Bayes GFlowNets Tiago da Silva Daniel Augusto R. M. A. de Souza Diego Mesquita BDL 41 0 0 08 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
Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning Yuxuan Ren Dihan Zheng Chang-Shu Liu Peiran Jin Yu Shi Lin Huang Jiyan He Shengjie Luo Tao Qin Tie-Yan Liu AI4CE 30 1 0 14 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
Latent Abstractions in Generative Diffusion Models Giulio Franzese Mattia Martini Giulio Corallo Paolo Papotti Pietro Michiardi DiffM 31 0 0 04 Oct 2024
NETS: A Non-Equilibrium Transport Sampler M. S. Albergo Eric Vanden-Eijnden DiffM 43 9 0 03 Oct 2024
Stochastic Sampling from Deterministic Flow Models Saurabh Singh Ian S. Fischer 34 2 0 03 Oct 2024
Equivariant score-based generative models provably learn distributions with symmetries efficiently Ziyu Chen M. Katsoulakis Benjamin J. Zhang DiffM 37 2 0 02 Oct 2024
HJ-sampler: A Bayesian sampler for inverse problems of a stochastic process by leveraging Hamilton-Jacobi PDEs and score-based generative models Tingwei Meng Zongren Zou Jérome Darbon George Karniadakis DiffM 40 2 0 15 Sep 2024
Neural Entropy Akhil Premkumar DiffM 21 0 0 05 Sep 2024
Iterated Energy-based Flow Matching for Sampling from Boltzmann Densities Dongyeop Woo Sungsoo Ahn 30 5 0 29 Aug 2024
Hamilton-Jacobi Reachability in Reinforcement Learning: A Survey Milan Ganai Sicun Gao Sylvia L. Herbert 32 6 0 12 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 34 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 31 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
A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization Sebastian Sanokowski Sepp Hochreiter Sebastian Lehner 27 17 0 03 Jun 2024
Learning to Approximate Particle Smoothing Trajectories via Diffusion Generative Models Ella Tamir Arno Solin DiffM 31 0 0 01 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 47 3 0 31 May 2024
Model-Based Diffusion for Trajectory Optimization Chaoyi Pan Zeji Yi Guanya Shi Guannan Qu 45 6 0 28 May 2024
Nonlinear denoising score matching for enhanced learning of structured distributions Jeremiah Birrell M. Katsoulakis Luc Rey-Bellet Benjamin J. Zhang Wei-wei Zhu DiffM 23 1 0 24 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 30 0 0 22 May 2024
Bridging discrete and continuous state spaces: Exploring the Ehrenfest process in time-continuous diffusion models Ludwig Winkler Lorenz Richter Manfred Opper 59 2 0 06 May 2024
Physics-Informed Diffusion Models Jan-Hendrik Bastek WaiChing Sun D. Kochmann DiffM AI4CE 47 10 0 21 Mar 2024
Soft-constrained Schrodinger Bridge: a Stochastic Control Approach Jhanvi Garg Xianyang Zhang Quan Zhou DiffM OT 35 0 0 04 Mar 2024
Generative Modelling with Tensor Train approximations of Hamilton--Jacobi--Bellman equations David Sommer Robert Gruhlke Max Kirstein Martin Eigel Claudia Schillings 22 3 0 23 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 39 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 Siddharth Gururani Sageev Oore Yisong Yue DiffM 48 21 0 22 Feb 2024
Stochastic Localization via Iterative Posterior Sampling Louis Grenioux Maxence Noble Marylou Gabrié Alain Durmus DiffM 38 12 0 16 Feb 2024
Particle Denoising Diffusion Sampler Angus Phillips Hai-Dang Dau M. Hutchinson Valentin De Bortoli George Deligiannidis Arnaud Doucet DiffM 54 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
Towards a Systems Theory of Algorithms Florian Dorfler Zhiyu He Giuseppe Belgioioso S. Bolognani John Lygeros Michael Muehlebach AI4CE 27 11 0 25 Jan 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
Energy based diffusion generator for efficient sampling of Boltzmann distributions Yan Wang Ling Guo Hao Wu Tao Zhou DiffM 34 3 0 04 Jan 2024
Stochastic Optimal Control Matching Carles Domingo-Enrich Jiequn Han Brandon Amos Joan Bruna Ricky T. Q. Chen DiffM 18 6 0 04 Dec 2023