Neural Ordinary Differential Equations

19 June 2018

Papers citing "Neural Ordinary Differential Equations"

50 / 914 papers shown

Title
Monotone operator equilibrium networks Ezra Winston J. Zico Kolter 32 130 0 15 Jun 2020
On Second Order Behaviour in Augmented Neural ODEs Alexander Norcliffe Cristian Bodnar Ben Day Nikola Simidjievski Pietro Lió 28 90 0 12 Jun 2020
Neural Ordinary Differential Equations on Manifolds Luca Falorsi Patrick Forré BDL AI4CE 6 33 0 11 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
Machine Learning and Control Theory A. Bensoussan Yiqun Li Dinh Phan Cao Nguyen M. Tran S. Yam Xiang Zhou AI4CE 24 12 0 10 Jun 2020
The Lipschitz Constant of Self-Attention Hyunjik Kim George Papamakarios A. Mnih 14 134 0 08 Jun 2020
SoftFlow: Probabilistic Framework for Normalizing Flow on Manifolds Hyeongju Kim Hyeonseung Lee Woohyun Kang Joun Yeop Lee N. Kim 3DPC 19 114 0 08 Jun 2020
The Power Spherical distribution Nicola De Cao Wilker Aziz 22 28 0 08 Jun 2020
Predictive Coding Approximates Backprop along Arbitrary Computation Graphs Beren Millidge Alexander Tschantz Christopher L. Buckley 24 118 0 07 Jun 2020
UFO-BLO: Unbiased First-Order Bilevel Optimization Valerii Likhosherstov Xingyou Song K. Choromanski Jared Davis Adrian Weller 32 7 0 05 Jun 2020
The Convolution Exponential and Generalized Sylvester Flows Emiel Hoogeboom Victor Garcia Satorras Jakub M. Tomczak Max Welling 25 28 0 02 Jun 2020
Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows Derek Onken Lars Ruthotto BDL 24 51 0 27 May 2020
Neural Controlled Differential Equations for Irregular Time Series Patrick Kidger James Morrill James Foster Terry Lyons AI4TS 25 449 0 18 May 2020
Deep Learning for Post-Processing Ensemble Weather Forecasts Peter Grönquist Chengyuan Yao Tal Ben-Nun Nikoli Dryden P. Dueben Shigang Li Torsten Hoefler 17 165 0 18 May 2020
Revealing hidden dynamics from time-series data by ODENet Pipi Hu Wuyue Yang Yi Zhu L. Hong AI4TS 24 35 0 11 May 2020
Physarum Powered Differentiable Linear Programming Layers and Applications Zihang Meng Sathya Ravi Vikas Singh 21 5 0 30 Apr 2020
RotEqNet: Rotation-Equivariant Network for Fluid Systems with Symmetric High-Order Tensors Liyao (Mars) Gao Yifan Du Hongshan Li Guang Lin 27 12 0 28 Apr 2020
Time Series Forecasting With Deep Learning: A Survey Bryan Lim S. Zohren AI4TS AI4CE 36 1,186 0 28 Apr 2020
Deep Learning for Time Series Forecasting: Tutorial and Literature Survey Konstantinos Benidis Syama Sundar Rangapuram Valentin Flunkert Bernie Wang Danielle C. Maddix ... David Salinas Lorenzo Stella François-Xavier Aubet Laurent Callot Tim Januschowski AI4TS 25 176 0 21 Apr 2020
DeepCFD: Efficient Steady-State Laminar Flow Approximation with Deep Convolutional Neural Networks M. Ribeiro A. Rehman Sheraz Ahmed Andreas Dengel 4 75 0 19 Apr 2020
CPR-GCN: Conditional Partial-Residual Graph Convolutional Network in Automated Anatomical Labeling of Coronary Arteries Han Yang Xingjian Zhen Ying Chi Lei Zhang Xiansheng Hua MedIm 16 43 0 19 Mar 2020
Stable Neural Flows Stefano Massaroli Michael Poli Michelangelo Bin Jinkyoo Park Atsushi Yamashita Hajime Asama 46 30 0 18 Mar 2020
Learning to Encode Position for Transformer with Continuous Dynamical Model Xuanqing Liu Hsiang-Fu Yu Inderjit Dhillon Cho-Jui Hsieh 8 107 0 13 Mar 2020
A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth Yiping Lu Chao Ma Yulong Lu Jianfeng Lu Lexing Ying MLT 36 78 0 11 Mar 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 130 424 0 10 Mar 2020
TIME: A Transparent, Interpretable, Model-Adaptive and Explainable Neural Network for Dynamic Physical Processes Gurpreet Singh Soumyajit Gupta Matt Lease Clint Dawson AI4TS AI4CE 19 2 0 05 Mar 2020
Methods to Recover Unknown Processes in Partial Differential Equations Using Data Zhen Chen Kailiang Wu D. Xiu 19 3 0 05 Mar 2020
Bayesian System ID: Optimal management of parameter, model, and measurement uncertainty Nicholas Galioto Alex Gorodetsky 9 32 0 04 Mar 2020
Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction Vincent Le Guen Nicolas Thome AI4CE PINN 89 288 0 03 Mar 2020
Learning Multivariate Hawkes Processes at Scale Maximilian Nickel Matt Le 32 17 0 28 Feb 2020
Differentiable Molecular Simulations for Control and Learning Wujie Wang Simon Axelrod Rafael Gómez-Bombarelli AI4CE 106 49 0 27 Feb 2020
Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data Marc Finzi Samuel Stanton Pavel Izmailov A. Wilson 17 316 0 25 Feb 2020
Stochasticity in Neural ODEs: An Empirical Study V. Oganesyan Alexandra Volokhova Dmitry Vetrov BDL 22 20 0 22 Feb 2020
Stochastic Latent Residual Video Prediction Jean-Yves Franceschi E. Delasalles Mickaël Chen Sylvain Lamprier Patrick Gallinari VGen 26 159 0 21 Feb 2020
Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN AI4CE 34 78 0 20 Feb 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models Chin-Wei Huang Laurent Dinh Aaron Courville DRL 31 87 0 17 Feb 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 57 176 0 16 Feb 2020
Hypernetwork approach to generating point clouds P. Spurek Sebastian Winczowski Jacek Tabor M. Zamorski Maciej Ziȩba Tomasz Trzciñski 3DPC 39 34 0 10 Feb 2020
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics Alexander Tong Jessie Huang Guy Wolf David van Dijk Smita Krishnaswamy 29 158 0 09 Feb 2020
Incorporating Symmetry into Deep Dynamics Models for Improved Generalization Rui Wang Robin G. Walters Rose Yu AI4CE 52 167 0 08 Feb 2020
How to train your neural ODE: the world of Jacobian and kinetic regularization Chris Finlay J. Jacobsen L. Nurbekyan Adam M. Oberman 11 294 0 07 Feb 2020
Linearly Constrained Neural Networks J. Hendriks Carl Jidling A. Wills Thomas B. Schon 16 33 0 05 Feb 2020
Learning to Control PDEs with Differentiable Physics Philipp Holl V. Koltun Nils Thuerey AI4CE PINN 44 185 0 21 Jan 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 38 300 0 08 Jan 2020
Mean-Field and Kinetic Descriptions of Neural Differential Equations Michael Herty T. Trimborn G. Visconti 33 6 0 07 Jan 2020
Scalable Gradients for Stochastic Differential Equations Xuechen Li Ting-Kam Leonard Wong Ricky T. Q. Chen David Duvenaud 17 310 0 05 Jan 2020
Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU Patrick Kidger Terry Lyons 29 83 0 03 Jan 2020
Machine Learning from a Continuous Viewpoint E. Weinan Chao Ma Lei Wu 23 102 0 30 Dec 2019
Discovery of Dynamics Using Linear Multistep Methods Rachael Keller Q. Du 31 36 0 29 Dec 2019
ODE-based Deep Network for MRI Reconstruction A. Yazdanpanah O. Afacan Simon K. Warfield OOD 10 3 0 27 Dec 2019