v1v2 (latest)

Theoretical guarantees for sampling and inference in generative models with latent diffusions

Annual Conference Computational Learning Theory (COLT), 2019

5 March 2019

Papers citing "Theoretical guarantees for sampling and inference in generative models with latent diffusions"

50 / 79 papers shown

Title
A Closed-Form Framework for Schrödinger Bridges Between Arbitrary Densities Hanwen Huang DiffM 144 0 0 11 Nov 2025
Rectified Noise: A Generative Model Using Positive-incentive Noise Zhenyu Gu Yanchen Xu Sida Huang Yubin Guo Hongyuan Zhang 189 3 0 11 Nov 2025
HardFlow: Hard-Constrained Sampling for Flow-Matching Models via Trajectory Optimization Zeyang Li Kaveh Alim Navid Azizan 264 0 0 11 Nov 2025
Functional Adjoint Sampler: Scalable Sampling on Infinite Dimensional Spaces Byoungwoo Park Juho Lee Guan-Horng Liu 124 0 0 09 Nov 2025
Balanced conic rectified flow Kim Shin Seong Mingi Kwon Jaeseok Jeong Youngjung Uh 80 2 0 29 Oct 2025
Trust Region Constrained Measure Transport in Path Space for Stochastic Optimal Control and Inference Denis Blessing Julius Berner Lorenz Richter Carles Domingo-Enrich Yuanqi Du Arash Vahdat Gerhard Neumann 104 5 0 17 Aug 2025
Path Integral Optimiser: Global Optimisation via Neural Schrödinger-Föllmer Diffusion Max McGuinness Eirik Fladmark Francisco Vargas 107 0 0 07 Jun 2025
Scientific machine learning in Hydrology: a unified perspectiveEarth Science Informatics (ESI), 2025 Adoubi Vincent De Paul Adombi AI4CE 82 0 0 24 May 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 468 30 0 16 Apr 2025
Bezier Distillation Ling Feng SK Yang 127 0 0 20 Mar 2025
Neural Guided Diffusion Bridges Gefan Yang Frank van der Meulen Stefan Sommer DiffM 270 1 0 17 Feb 2025
Neural Flow Samplers with Shortcut Models Wuhao Chen Chinmay Pani Yingzhen Li 584 2 0 11 Feb 2025
CAFuser: Condition-Aware Multimodal Fusion for Robust Semantic Perception of Driving ScenesIEEE Robotics and Automation Letters (RA-L), 2024 Tim Broedermann Daniel Gehrig Yuqian Fu Luc Van Gool 285 26 0 28 Jan 2025
Learned Reference-based Diffusion Sampling for multi-modal distributions Maxence Noble Louis Grenioux Marylou Gabrié Alain Durmus DiffM 408 11 0 25 Oct 2024
How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral FrameworkInternational Conference on Learning Representations (ICLR), 2024 Yinuo Ren Haoxuan Chen Grant M. Rotskoff Lexing Ying 251 25 0 04 Oct 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 296 0 0 07 Aug 2024
Log-Concave Coupling for Sampling Neural Net Posteriors Curtis McDonald Andrew R. Barron 106 1 0 26 Jul 2024
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference Jian Xu Delu Zeng John Paisley DiffM 225 11 0 24 Jul 2024
Stochastic Optimal Control for Diffusion Bridges in Function Spaces Byoungwoo Park Jungwon Choi Sungbin Lim Juho Lee 465 8 0 31 May 2024
Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time ComplexityNeural Information Processing Systems (NeurIPS), 2024 Haoxuan Chen Yinuo Ren Lexing Ying Grant M. Rotskoff 259 36 0 24 May 2024
Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing FlowsNeural Information Processing Systems (NeurIPS), 2024 A. Cabezas Louis Sharrock Christopher Nemeth 205 7 0 23 May 2024
Control, Transport and Sampling: Towards Better Loss Design Qijia Jiang David Nabergoj OT 192 0 0 22 May 2024
Directly Denoising Diffusion Models Dan Zhang Jingjing Wang Feng Luo DiffM 286 2 0 22 May 2024
One-step data-driven generative model via Schrödinger Bridge Hanwen Huang DiffM 193 4 0 21 May 2024
Mixing Artificial and Natural Intelligence: From Statistical Mechanics to AI and Back to Turbulence Michael Chertkov AI4CE 290 4 0 26 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 312 35 0 20 Mar 2024
Soft-constrained Schrodinger Bridge: a Stochastic Control Approach Jhanvi Garg Xianyang Zhang Quan Zhou DiffM OT 265 5 0 04 Mar 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 247 80 0 23 Feb 2024
Stochastic Localization via Iterative Posterior Sampling Louis Grenioux Maxence Noble Marylou Gabrié Alain Durmus DiffM 272 21 0 16 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 228 85 0 09 Feb 2024
Implicit Diffusion: Efficient Optimization through Stochastic Sampling Pierre Marion Anna Korba Peter Bartlett Mathieu Blondel Valentin De Bortoli Arnaud Doucet Felipe Llinares-López Courtney Paquette Quentin Berthet 355 19 0 08 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 590 41 0 07 Feb 2024
Towards a Systems Theory of AlgorithmsIEEE Control Systems Letters (L-CSS), 2024 Florian Dorfler Zhiyu He Giuseppe Belgioioso S. Bolognani John Lygeros Michael Muehlebach AI4CE 229 24 0 25 Jan 2024
Neural Stochastic Differential Equations with Change Points: A Generative Adversarial Approach Zhongchang Sun Yousef El-Laham Svitlana Vyetrenko AI4TS 211 2 0 20 Dec 2023
Noise in the reverse process improves the approximation capabilities of diffusion models Karthik Elamvazhuthi Samet Oymak Fabio Pasqualetti DiffM 170 0 0 13 Dec 2023
Efficient Dataset Distillation via Minimax DiffusionComputer Vision and Pattern Recognition (CVPR), 2023 Jianyang Gu Saeed Vahidian Vyacheslav Kungurtsev Haonan Wang Wei Jiang Yang You Yiran Chen DD 256 60 0 27 Nov 2023
Neural Structure Learning with Stochastic Differential EquationsInternational Conference on Learning Representations (ICLR), 2023 Benjie Wang Joel Jennings Wenbo Gong CML AI4TS 212 9 0 06 Nov 2023
Convergence of flow-based generative models via proximal gradient descent in Wasserstein spaceIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2023 Xiuyuan Cheng Jianfeng Lu Yixin Tan Yao Xie 522 29 0 26 Oct 2023
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimizationInternational Conference on Learning Representations (ICLR), 2023 Dinghuai Zhang Ricky Tian Qi Chen Cheng-Hao Liu Aaron C. Courville Yoshua Bengio 347 59 0 04 Oct 2023
Diffusion Schrödinger Bridges for Bayesian Computation J. Heng Valentin De Bortoli Arnaud Doucet DiffM 152 3 0 27 Aug 2023
Reverse Diffusion Monte CarloInternational Conference on Learning Representations (ICLR), 2023 Xunpeng Huang Hanze Dong Yi Hao Yi-An Ma Tong Zhang DiffM 393 35 0 05 Jul 2023
Improved sampling via learned diffusionsInternational Conference on Learning Representations (ICLR), 2023 Lorenz Richter Julius Berner DiffM 350 88 0 03 Jul 2023
Transport meets Variational Inference: Controlled Monte Carlo DiffusionsInternational Conference on Learning Representations (ICLR), 2023 Francisco Vargas Shreyas Padhy Denis Blessing Nikolas Nusken DiffM OT 757 12 0 03 Jul 2023
A Constructive Approach to Function Realization by Neural Stochastic Differential EquationsIEEE Conference on Decision and Control (CDC), 2023 Tanya Veeravalli Maxim Raginsky 128 0 0 01 Jul 2023
Latent SDEs on Homogeneous SpacesNeural Information Processing Systems (NeurIPS), 2023 Sebastian Zeng Florian Graf Roland Kwitt BDL 292 12 0 28 Jun 2023
On a Class of Gibbs Sampling over NetworksAnnual Conference Computational Learning Theory (COLT), 2023 Bo Yuan JiaoJiao Fan Jiaming Liang Andre Wibisono Yongxin Chen 173 8 0 23 Jun 2023
On the Design Fundamentals of Diffusion Models: A SurveyPattern Recognition (Pattern Recogn.), 2023 Ziyi Chang George Alex Koulieris Hyung Jin Chang Hubert P. H. Shum DiffM 545 78 0 07 Jun 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 290 1 0 16 May 2023
Directed Chain Generative Adversarial NetworksInternational Conference on Machine Learning (ICML), 2023 Ming Min Ruimeng Hu Tomoyuki Ichiba AI4TS AI4CE GAN 209 1 0 25 Apr 2023
Denoising Diffusion SamplersInternational Conference on Learning Representations (ICLR), 2023 Francisco Vargas Will Grathwohl Arnaud Doucet DiffM 279 119 0 27 Feb 2023