Monge-Ampère Flow for Generative Modeling

26 September 2018

Lei Wang

Papers citing "Monge-Ampère Flow for Generative Modeling"

47 / 47 papers shown

Title
Accurate and thermodynamically consistent hydrogen equation of state for planetary modeling with flow matching Hao Xie Saburo Howard Guglielmo Mazzola 41 1 0 17 Jan 2025
How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework Yinuo Ren Haoxuan Chen Grant M. Rotskoff Lexing Ying 52 3 0 04 Oct 2024
Gaussian Interpolation Flows Yuan Gao Jianxia Huang Yuling Jiao AI4CE 25 2 0 20 Nov 2023
PINF: Continuous Normalizing Flows for Physics-Constrained Deep Learning Feng Liu Faguo Wu Xiao Zhang AI4CE 21 2 0 26 Sep 2023
Stochastic Interpolants: A Unifying Framework for Flows and Diffusions M. S. Albergo Nicholas M. Boffi Eric Vanden-Eijnden DiffM 257 268 0 15 Mar 2023
Normalizing flow neural networks by JKO scheme Chen Xu Xiuyuan Cheng Yao Xie 39 24 0 29 Dec 2022
A Mathematical Framework for Learning Probability Distributions Hongkang Yang 31 7 0 22 Dec 2022
High-dimensional density estimation with tensorizing flow Yinuo Ren Hongli Zhao Y. Khoo Lexing Ying 10 9 0 01 Dec 2022
Taming Hyperparameter Tuning in Continuous Normalizing Flows Using the JKO Scheme Alexander Vidal Samy Wu Fung Luis Tenorio Stanley Osher L. Nurbekyan 35 15 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 32 33 0 14 Nov 2022
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian Preserving Flows G. Morel Lucas Drumetz Simon Benaïchouche Nicolas Courty F. Rousseau OT 30 6 0 22 Sep 2022
Deep Variational Free Energy Approach to Dense Hydrogen H.-j. Xie Ziqun Li Han Wang Linfeng Zhang Lei Wang 47 9 0 13 Sep 2022
Multisymplectic Formulation of Deep Learning Using Mean--Field Type Control and Nonlinear Stability of Training Algorithm Nader Ganaba 16 0 0 07 Jul 2022
Characteristic Neural Ordinary Differential Equations Xingzi Xu Ali Hasan Khalil Elkhalil Jie Ding Vahid Tarokh BDL 29 3 0 25 Nov 2021
Augmented KRnet for density estimation and approximation Xiaoliang Wan Keju Tang 17 5 0 26 May 2021
Ab-initio study of interacting fermions at finite temperature with neural canonical transformation Hao Xie Linfeng Zhang Lei Wang 20 26 0 18 May 2021
Adaptive deep density approximation for Fokker-Planck equations Keju Tang Xiaoliang Wan Qifeng Liao 31 37 0 20 Mar 2021
An Introduction to Deep Generative Modeling Lars Ruthotto E. Haber AI4CE 33 220 0 09 Mar 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models Sam Bond-Taylor Adam Leach Yang Long Chris G. Willcocks VLM TPM 41 483 0 08 Mar 2021
EBMs Trained with Maximum Likelihood are Generator Models Trained with a Self-adverserial Loss Zhisheng Xiao Qing Yan Y. Amit 32 2 0 23 Feb 2021
Jacobian Determinant of Normalizing Flows Huadong Liao Jiawei He DRL 19 7 0 12 Feb 2021
Generative Learning With Euler Particle Transport Yuan Gao Jian Huang Yuling Jiao Jin Liu Xiliang Lu J. Yang OT 28 2 0 11 Dec 2020
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization Chin-Wei Huang Ricky T. Q. Chen Christos Tsirigotis Aaron Courville OT 119 95 0 10 Dec 2020
Generalization and Memorization: The Bias Potential Model Hongkang Yang E. Weinan 25 11 0 29 Nov 2020
Training Invertible Linear Layers through Rank-One Perturbations Andreas Krämer Jonas Köhler Frank Noé 16 0 0 14 Oct 2020
CaSPR: Learning Canonical Spatiotemporal Point Cloud Representations Davis Rempe Tolga Birdal Yongheng Zhao Zan Gojcic Srinath Sridhar Leonidas J. Guibas 3DPC 29 71 0 06 Aug 2020
VAE-KRnet and its applications to variational Bayes Xiaoliang Wan Shuangqing Wei BDL DRL 19 13 0 29 Jun 2020
Learning normalizing flows from Entropy-Kantorovich potentials Chris Finlay Augusto Gerolin Adam M. Oberman Aram-Alexandre Pooladian 33 23 0 10 Jun 2020
Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities Jonas Köhler Leon Klein Frank Noé DRL 29 259 0 03 Jun 2020
The Expressive Power of a Class of Normalizing Flow Models Zhifeng Kong Kamalika Chaudhuri TPM 18 51 0 31 May 2020
OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport Derek Onken Samy Wu Fung Xingjian Li Lars Ruthotto OT 18 156 0 29 May 2020
A Triangular Network For Density Estimation Xi-Lin Li TPM 11 1 0 30 Apr 2020
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 183 761 0 13 Mar 2020
Differentiable Molecular Simulations for Control and Learning Wujie Wang Simon Axelrod Rafael Gómez-Bombarelli AI4CE 109 49 0 27 Feb 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 57 176 0 16 Feb 2020
Learning Implicit Generative Models with Theoretical Guarantees Yuan Gao Jian Huang Yuling Jiao Jin Liu 25 7 0 07 Feb 2020
How to train your neural ODE: the world of Jacobian and kinetic regularization Chris Finlay J. Jacobsen L. Nurbekyan Adam M. Oberman 11 296 0 07 Feb 2020
Deep Learning via Dynamical Systems: An Approximation Perspective Qianxiao Li Ting Lin Zuowei Shen AI4TS AI4CE 25 107 0 22 Dec 2019
A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems Lars Ruthotto Stanley Osher Wuchen Li L. Nurbekyan Samy Wu Fung AI4CE 28 214 0 04 Dec 2019
Review: Ordinary Differential Equations For Deep Learning Xinshi Chen AI4TS AI4CE 20 5 0 01 Nov 2019
Neural Density Estimation and Likelihood-free Inference George Papamakarios BDL DRL 24 44 0 29 Oct 2019
Neural Canonical Transformation with Symplectic Flows Shuo-Hui Li Chen Dong Linfeng Zhang Lei Wang DRL 34 28 0 30 Sep 2019
On the Need for Topology-Aware Generative Models for Manifold-Based Defenses Uyeong Jang Susmit Jha S. Jha AAML 27 13 0 07 Sep 2019
Exponential Family Estimation via Adversarial Dynamics Embedding Bo Dai Ziqiang Liu H. Dai Niao He Arthur Gretton Le Song Dale Schuurmans 18 52 0 27 Apr 2019
Particle Flow Bayes' Rule Xinshi Chen H. Dai Le Song 14 9 0 02 Feb 2019
Coupling the reduced-order model and the generative model for an importance sampling estimator Xiaoliang Wan Shuangqing Wei 16 10 0 23 Jan 2019
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 272 2,552 0 25 Jan 2016