Stochastic Normalizing Flows

16 February 2020

Frank Noé

Papers citing "Stochastic Normalizing Flows"

50 / 122 papers shown

Title
Adaptive Annealed Importance Sampling with Constant Rate Progress Shirin Goshtasbpour Victor Cohen F. Pérez-Cruz 13 7 0 27 Jun 2023
Equivariant flow matching Leon Klein Andreas Krämer Frank Noé 16 59 0 26 Jun 2023
Enhanced Sampling with Machine Learning: A Review S. Mehdi Zachary Smith Lukas Herron Ziyue Zou P. Tiwary AI4CE 11 8 0 15 Jun 2023
Entropy-based Training Methods for Scalable Neural Implicit Sampler Weijian Luo Boya Zhang Zhihua Zhang 21 10 0 08 Jun 2023
Non-adversarial training of Neural SDEs with signature kernel scores Zacharia Issa Blanka Horvath M. Lemercier C. Salvi AI4TS 27 24 0 25 May 2023
Normalizing flow sampling with Langevin dynamics in the latent space Florentin Coeurdoux N. Dobigeon P. Chainais DRL 11 7 0 20 May 2023
Generative Sliced MMD Flows with Riesz Kernels J. Hertrich Christian Wald Fabian Altekrüger Paul Hagemann 28 23 0 19 May 2023
Piecewise Normalizing Flows H. Bevins Will Handley Thomas Gessey-Jones 20 0 0 04 May 2023
A mean-field games laboratory for generative modeling Benjamin J. Zhang M. Katsoulakis 22 17 0 26 Apr 2023
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems Ziruo Cai Junqi Tang Subhadip Mukherjee Jinglai Li Carola Bibiane Schönlieb Xiaoqun Zhang AI4CE 28 3 0 17 Apr 2023
Neural Diffeomorphic Non-uniform B-spline Flows S. Hong S. Chun 22 1 0 07 Apr 2023
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems Fabian Altekrüger Paul Hagemann Gabriele Steidl TPM 21 9 0 28 Mar 2023
Eryn : A multi-purpose sampler for Bayesian inference N. Karnesis Michael L. Katz N. Korsakova J. Gair N. Stergioulas 8 28 0 03 Mar 2023
Denoising Diffusion Samplers Francisco Vargas Will Grathwohl Arnaud Doucet DiffM 19 75 0 27 Feb 2023
Modeling Polypharmacy and Predicting Drug-Drug Interactions using Deep Generative Models on Multimodal Graphs Nhat-Khang Ngô Truong Son-Hy Risi Kondor GNN BDL 11 1 0 17 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 24 79 0 30 Jan 2023
Neural Wasserstein Gradient Flows for Maximum Mean Discrepancies with Riesz Kernels Fabian Altekrüger J. Hertrich Gabriele Steidl 27 13 0 27 Jan 2023
Rigid Body Flows for Sampling Molecular Crystal Structures Jonas Köhler Michele Invernizzi P. D. Haan Frank Noé AI4CE 25 27 0 26 Jan 2023
normflows: A PyTorch Package for Normalizing Flows Vincent Stimper David Liu Andrew Campbell V. Berenz Lukas Ryll Bernhard Schölkopf José Miguel Hernández-Lobato AI4CE 14 55 0 26 Jan 2023
Learning Interpolations between Boltzmann Densities Bálint Máté Franccois Fleuret 14 23 0 18 Jan 2023
Designing losses for data-free training of normalizing flows on Boltzmann distributions Loris Felardos Jérôme Hénin Guillaume Charpiat AI4CE 16 8 0 13 Jan 2023
On the Robustness of Normalizing Flows for Inverse Problems in Imaging Seongmin Hong I. Park S. Chun 23 7 0 08 Dec 2022
Accelerating Inverse Learning via Intelligent Localization with Exploratory Sampling Jiaxin Zhang Sirui Bi Victor Fung 17 3 0 02 Dec 2022
Proximal Residual Flows for Bayesian Inverse Problems J. Hertrich BDL TPM 23 4 0 30 Nov 2022
Aspects of scaling and scalability for flow-based sampling of lattice QCD Ryan Abbott M. S. Albergo Aleksandar Botev D. Boyda Kyle Cranmer ... Ali Razavi Danilo Jimenez Rezende F. Romero-López P. Shanahan Julian M. Urban 22 33 0 14 Nov 2022
An optimal control perspective on diffusion-based generative modeling Julius Berner Lorenz Richter Karen Ullrich DiffM 23 80 0 02 Nov 2022
Blind Super-Resolution for Remote Sensing Images via Conditional Stochastic Normalizing Flows Hanlin Wu Ning Ni Shan Wang Li-bao Zhang 30 8 0 14 Oct 2022
Optimization of Annealed Importance Sampling Hyperparameters Shirin Goshtasbpour F. Pérez-Cruz 13 1 0 27 Sep 2022
Local_INN: Implicit Map Representation and Localization with Invertible Neural Networks Zirui Zang Hongrui Zheng Johannes Betz Rahul Mangharam 21 6 0 24 Sep 2022
Predicting Drug-Drug Interactions using Deep Generative Models on Graphs Nhat-Khang Ngô Truong Son-Hy Risi Kondor BDL GNN 20 3 0 14 Sep 2022
Diffusion Models: A Comprehensive Survey of Methods and Applications Ling Yang Zhilong Zhang Yingxia Shao Shenda Hong Runsheng Xu Yue Zhao Wentao Zhang Bin Cui Ming-Hsuan Yang DiffM MedIm 224 1,296 0 02 Sep 2022
Langevin Diffusion Variational Inference Tomas Geffner Justin Domke DiffM 9 19 0 16 Aug 2022
Score-Based Diffusion meets Annealed Importance Sampling Arnaud Doucet Will Grathwohl A. G. Matthews Heiko Strathmann DiffM 28 43 0 16 Aug 2022
Flow Annealed Importance Sampling Bootstrap Laurence Illing Midgley Vincent Stimper G. Simm Bernhard Schölkopf José Miguel Hernández-Lobato 16 77 0 03 Aug 2022
Conditioning Normalizing Flows for Rare Event Sampling S. Falkner A. Coretti Salvatore Romano P. Geissler C. Dellago 14 12 0 29 Jul 2022
Gradients should stay on Path: Better Estimators of the Reverse- and Forward KL Divergence for Normalizing Flows Lorenz Vaitl K. Nicoli Shinichi Nakajima Pan Kessel 42 24 0 17 Jul 2022
Text to Image Synthesis using Stacked Conditional Variational Autoencoders and Conditional Generative Adversarial Networks Haileleol Tibebu Aadin Malik V. D. Silva GAN 18 7 0 06 Jul 2022
Can Push-forward Generative Models Fit Multimodal Distributions? Antoine Salmona Valentin De Bortoli J. Delon A. Desolneux DiffM 21 36 0 29 Jun 2022
Learning Optimal Flows for Non-Equilibrium Importance Sampling Yu Cao Eric Vanden-Eijnden 8 3 0 20 Jun 2022
E2V-SDE: From Asynchronous Events to Fast and Continuous Video Reconstruction via Neural Stochastic Differential Equations Jongwan Kim Dongjin Lee Byunggook Na Seongsik Park Jeonghee Jo Sung-Hoon Yoon 29 0 0 15 Jun 2022
A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model Jianwen Xie Y. Zhu J. Li Ping Li 16 50 0 13 May 2022
Mixed Effects Neural ODE: A Variational Approximation for Analyzing the Dynamics of Panel Data Jurijs Nazarovs Rudrasis Chakraborty Songwong Tasneeyapant Sathya Ravi Vikas Singh 12 4 0 18 Feb 2022
Continual Repeated Annealed Flow Transport Monte Carlo A. G. Matthews Michael Arbel Danilo Jimenez Rezende Arnaud Doucet OT 24 46 0 31 Jan 2022
Path Integral Sampler: a stochastic control approach for sampling Qinsheng Zhang Yongxin Chen DiffM 13 101 0 30 Nov 2021
Generalized Normalizing Flows via Markov Chains Paul Hagemann J. Hertrich Gabriele Steidl BDL DiffM AI4CE 22 22 0 24 Nov 2021
Bootstrap Your Flow Laurence Illing Midgley Vincent Stimper G. Simm José Miguel Hernández-Lobato 15 5 0 22 Nov 2021
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling Greg Ver Steeg Aram Galstyan 20 13 0 03 Nov 2021
Resampling Base Distributions of Normalizing Flows Vincent Stimper Bernhard Schölkopf José Miguel Hernández-Lobato BDL 22 32 0 29 Oct 2021
Diffusion Normalizing Flow Qinsheng Zhang Yongxin Chen DiffM 21 87 0 14 Oct 2021
Smooth Normalizing Flows Jonas Köhler Andreas Krämer Frank Noé 13 53 0 01 Oct 2021