Neural Ordinary Differential Equations

19 June 2018

Papers citing "Neural Ordinary Differential Equations"

50 / 944 papers shown

Title
Bayesian System ID: Optimal management of parameter, model, and measurement uncertainty Nicholas Galioto Alex Gorodetsky 11 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
Differentiating through the Fréchet Mean Aaron Lou Isay Katsman Qingxuan Jiang Serge J. Belongie Ser-Nam Lim Christopher De Sa DRL 18 61 0 29 Feb 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 19 316 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 42 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 29 159 0 09 Feb 2020
Incorporating Symmetry into Deep Dynamics Models for Improved Generalization Rui Wang Robin G. Walters Rose Yu AI4CE 52 168 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 11 296 0 07 Feb 2020
Linearly Constrained Neural Networks J. Hendriks Carl Jidling A. Wills Thomas B. Schon 16 34 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 36 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 32 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
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing V. Monga Yuelong Li Yonina C. Eldar 31 999 0 22 Dec 2019
Deep Learning via Dynamical Systems: An Approximation Perspective Qianxiao Li Ting Lin Zuowei Shen AI4TS AI4CE 14 107 0 22 Dec 2019
Multilevel Initialization for Layer-Parallel Deep Neural Network Training E. Cyr Stefanie Günther J. Schroder AI4CE 14 11 0 19 Dec 2019
InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers T. Nguyen Animesh Garg Richard G. Baraniuk Anima Anandkumar TPM 28 9 0 09 Dec 2019
Continuous Graph Neural Networks Louis-Pascal Xhonneux Meng Qu Jian Tang GNN 24 149 0 02 Dec 2019
Enabling real-time multi-messenger astrophysics discoveries with deep learning Eliu A. Huerta Gabrielle Allen I. Andreoni J. Antelis E. Bachelet ... Wei Wei J. Wells T. Williams Jinjun Xiong Zhizhen Zhao AI4CE 25 71 0 26 Nov 2019
Graph Neural Ordinary Differential Equations Michael Poli Stefano Massaroli Junyoung Park Atsushi Yamashita Hajime Asama Jinkyoo Park AI4CE 42 154 0 18 Nov 2019
Shadowing Properties of Optimization Algorithms Antonio Orvieto Aurelien Lucchi 27 18 0 12 Nov 2019
Physics-Informed Neural Networks for Power Systems George S. Misyris Andreas Venzke Spyros Chatzivasileiadis PINN AI4CE 12 212 0 09 Nov 2019
Decomposable-Net: Scalable Low-Rank Compression for Neural Networks A. Yaguchi Taiji Suzuki Shuhei Nitta Y. Sakata A. Tanizawa 19 9 0 29 Oct 2019
Neural Similarity Learning Weiyang Liu Zhen Liu James M. Rehg Le Song 27 29 0 28 Oct 2019
FD-Net with Auxiliary Time Steps: Fast Prediction of PDEs using Hessian-Free Trust-Region Methods Nur Sila Gulgec Zheng Shi Neil Deshmukh S. Pakzad Martin Takáč 23 6 0 28 Oct 2019
Towards Robust and Stable Deep Learning Algorithms for Forward Backward Stochastic Differential Equations Batuhan Güler Alexis Laignelet P. Parpas OOD 21 16 0 25 Oct 2019
Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands H. Pinckaers G. Litjens SSeg MedIm 14 36 0 23 Oct 2019
Machine learning and serving of discrete field theories -- when artificial intelligence meets the discrete universe H. Qin 26 30 0 22 Oct 2019
Why bigger is not always better: on finite and infinite neural networks Laurence Aitchison 175 51 0 17 Oct 2019
On Robustness of Neural Ordinary Differential Equations Hanshu Yan Jiawei Du Vincent Y. F. Tan Jiashi Feng OOD 19 138 0 12 Oct 2019
Hamiltonian Generative Networks Peter Toth Danilo Jimenez Rezende Andrew Jaegle S. Racanière Aleksandar Botev I. Higgins BDL DRL AI4CE GAN 21 215 0 30 Sep 2019
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 149 220 0 29 Sep 2019
Hamiltonian Graph Networks with ODE Integrators Alvaro Sanchez-Gonzalez V. Bapst Kyle Cranmer Peter W. Battaglia AI4CE 20 176 0 27 Sep 2019
Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN 54 268 0 26 Sep 2019
Neural Dynamics on Complex Networks Chengxi Zang Fei-Yue Wang AI4CE 27 68 0 18 Aug 2019
Implicit Deep Learning L. Ghaoui Fangda Gu Bertrand Travacca Armin Askari Alicia Y. Tsai AI4CE 34 176 0 17 Aug 2019
Matrix Lie Maps and Neural Networks for Solving Differential Equations A. Ivanov S. Andrianov 22 3 0 16 Aug 2019
Unconstrained Monotonic Neural Networks Antoine Wehenkel Gilles Louppe TPM 26 146 0 14 Aug 2019
Wasserstein Robust Reinforcement Learning Mohammed Abdullah Hang Ren Haitham Bou-Ammar Vladimir Milenkovic Rui Luo Mingtian Zhang Jun Wang 32 75 0 30 Jul 2019