How to train your neural ODE: the world of Jacobian and kinetic regularization

7 February 2020

Papers citing "How to train your neural ODE: the world of Jacobian and kinetic regularization"

31 / 31 papers shown

Title
Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks Ziqiang Liu Xiaoda Wang Bohan Wang Zijie Huang Carl Yang Wei Jin AI4TS AI4CE 477 1 0 29 Mar 2025
Local Flow Matching Generative Models Chen Xu Xiuyuan Cheng Yao Xie 90 2 0 03 Jan 2025
Neural Differential Appearance Equations Chen Liu Tobias Ritschel 59 0 0 23 Sep 2024
Building symmetries into data-driven manifold dynamics models for complex flows: application to two-dimensional Kolmogorov flow Carlos E. Pérez De Jesús Alec J. Linot Michael D. Graham AI4CE 65 2 0 15 Dec 2023
Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space Yiheng Jiang Sinho Chewi Aram-Alexandre Pooladian 114 8 0 05 Dec 2023
Enhancing Low-Order Discontinuous Galerkin Methods with Neural Ordinary Differential Equations for Compressible Navier--Stokes Equations Shinhoo Kang Emil M. Constantinescu AI4CE 57 0 0 29 Oct 2023
Probabilistic Learning of Multivariate Time Series with Temporal Irregularity Yijun Li Cheuk Hang Leung Qi Wu AI4TS 64 1 0 15 Jun 2023
Computing high-dimensional optimal transport by flow neural networks Chen Xu Xiuyuan Cheng Yao Xie OT 91 5 0 19 May 2023
Simple Video Generation using Neural ODEs David Kanaa Vikram S. Voleti Samira Ebrahimi Kahou Christopher Pal 46 20 0 07 Sep 2021
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 112 219 0 04 Dec 2019
Equivariant Flows: sampling configurations for multi-body systems with symmetric energies Jonas Köhler Leon Klein Frank Noé 79 91 0 02 Oct 2019
Potential Flow Generator with $L_2$ Optimal Transport Regularity for Generative Models Liu Yang George Karniadakis OT 35 43 0 29 Aug 2019
Residual Flows for Invertible Generative Modeling Ricky T. Q. Chen Jens Behrmann David Duvenaud J. Jacobsen BDL TPM DRL 106 377 0 06 Jun 2019
ODE $^2$ VAE: Deep generative second order ODEs with Bayesian neural networks Çağatay Yıldız Markus Heinonen Harri Lähdesmäki BDL DRL 63 88 0 27 May 2019
Neural ODEs with stochastic vector field mixtures Niall Twomey Michał Kozłowski Raúl Santos-Rodríguez 38 4 0 23 May 2019
Augmented Neural ODEs Emilien Dupont Arnaud Doucet Yee Whye Teh BDL 144 628 0 02 Apr 2019
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design Jonathan Ho Xi Chen A. Srinivas Yan Duan Pieter Abbeel DRL 82 449 0 01 Feb 2019
Invertible Residual Networks Jens Behrmann Will Grathwohl Ricky T. Q. Chen David Duvenaud J. Jacobsen UQCV TPM 120 623 0 02 Nov 2018
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models Will Grathwohl Ricky T. Q. Chen J. Bettencourt Ilya Sutskever David Duvenaud DRL 139 873 0 02 Oct 2018
Monge-Ampère Flow for Generative Modeling Linfeng Zhang E. Weinan Lei Wang DRL 81 63 0 26 Sep 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 292 3,129 0 09 Jul 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 411 5,103 0 19 Jun 2018
Deep Neural Networks Motivated by Partial Differential Equations Lars Ruthotto E. Haber AI4CE 118 490 0 12 Apr 2018
Sensitivity and Generalization in Neural Networks: an Empirical Study Roman Novak Yasaman Bahri Daniel A. Abolafia Jeffrey Pennington Jascha Narain Sohl-Dickstein AAML 93 439 0 23 Feb 2018
Progressive Growing of GANs for Improved Quality, Stability, and Variation Tero Karras Timo Aila S. Laine J. Lehtinen GAN 134 7,353 0 27 Oct 2017
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour Priya Goyal Piotr Dollár Ross B. Girshick P. Noordhuis Lukasz Wesolowski Aapo Kyrola Andrew Tulloch Yangqing Jia Kaiming He 3DH 126 3,678 0 08 Jun 2017
Stable Architectures for Deep Neural Networks E. Haber Lars Ruthotto 145 728 0 09 May 2017
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 263 3,696 0 26 May 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 466 2,568 0 25 Jan 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 193,878 0 10 Dec 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.8K 150,039 0 22 Dec 2014