Normalizing flow neural networks by JKO scheme

29 December 2022

Yao Xie

Papers citing "Normalizing flow neural networks by JKO scheme"

33 / 33 papers shown

Title
Liouville PDE-based sliced-Wasserstein flow for fair regression Pilhwa Lee Jayshawn Cooper 71 0 0 22 May 2025
Energy Matching: Unifying Flow Matching and Energy-Based Models for Generative Modeling Michal Balcerak Tamaz Amiranashvili Suprosanna Shit Antonio Terpin Lea Bogensperger Sebastian Kaltenbach Petros Koumoutsakos Bjoern Menze DiffM 102 3 0 14 Apr 2025
Can We Detect Failures Without Failure Data? Uncertainty-Aware Runtime Failure Detection for Imitation Learning Policies Chen Xu Tony Nguyen Emma Dixon Christopher Rodriguez Patrick Miller Robert Lee Paarth Shah Rares Andrei Ambrus Haruki Nishimura Masha Itkina OffRL 207 2 0 11 Mar 2025
Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow Models Rafał Karczewski Markus Heinonen Vikas Garg DiffM 86 1 0 09 Feb 2025
Local Flow Matching Generative Models Chen Xu Xiuyuan Cheng Yao Xie 72 2 0 03 Jan 2025
Score-based Neural Ordinary Differential Equations for Computing Mean Field Control Problems Mo Zhou Stanley Osher Wuchen Li 107 4 0 24 Sep 2024
Importance Corrected Neural JKO Sampling Johannes Hertrich Robert Gruhlke 80 2 0 29 Jul 2024
Computing high-dimensional optimal transport by flow neural networks Chen Xu Xiuyuan Cheng Yao Xie OT 78 5 0 19 May 2023
Taming Hyperparameter Tuning in Continuous Normalizing Flows Using the JKO Scheme Alexander Vidal Samy Wu Fung Luis Tenorio Stanley Osher L. Nurbekyan 63 20 0 30 Nov 2022
Probability flow solution of the Fokker-Planck equation Nicholas M. Boffi Eric Vanden-Eijnden 47 45 0 09 Jun 2022
Variational Wasserstein gradient flow JiaoJiao Fan Qinsheng Zhang Amirhossein Taghvaei Yongxin Chen 113 57 0 04 Dec 2021
Diffusion Normalizing Flow Qinsheng Zhang Yongxin Chen DiffM 51 91 0 14 Oct 2021
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks David Alvarez-Melis Yair Schiff Youssef Mroueh 63 56 0 01 Jun 2021
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 292 6,409 0 26 Nov 2020
StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flows Rameen Abdal Peihao Zhu Niloy Mitra Peter Wonka 84 531 0 06 Aug 2020
Riemannian Continuous Normalizing Flows Emile Mathieu Maximilian Nickel AI4CE 67 124 0 18 Jun 2020
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 88 218 0 04 Dec 2019
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 213 3,870 0 12 Jul 2019
Graph Normalizing Flows Jenny Liu Aviral Kumar Jimmy Ba J. Kiros Kevin Swersky BDL GNN AI4CE 70 164 0 30 May 2019
Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit Belinda Tzen Maxim Raginsky DiffM 142 209 0 23 May 2019
Fast Graph Representation Learning with PyTorch Geometric Matthias Fey J. E. Lenssen 3DH GNN 3DPC 193 4,326 0 06 Mar 2019
Theoretical guarantees for sampling and inference in generative models with latent diffusions Belinda Tzen Maxim Raginsky DiffM 59 101 0 05 Mar 2019
Monge-Ampère Flow for Generative Modeling Linfeng Zhang E. Weinan Lei Wang DRL 75 63 0 26 Sep 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 267 3,124 0 09 Jul 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 339 5,081 0 19 Jun 2018
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 175 1,349 0 19 May 2017
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 171 9,533 0 31 Mar 2017
On the ability of neural nets to express distributions Holden Lee Rong Ge Tengyu Ma Andrej Risteski Sanjeev Arora BDL 64 84 0 22 Feb 2017
Input Convex Neural Networks Brandon Amos Lei Xu J. Zico Kolter 272 619 0 22 Sep 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 63 1,091 0 16 Aug 2016
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering M. Defferrard Xavier Bresson P. Vandergheynst GNN 306 7,646 0 30 Jun 2016
Improved Techniques for Training GANs Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen GAN 456 9,027 0 10 Jun 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 235 3,689 0 26 May 2016