Neural Ordinary Differential Equations

19 June 2018

Papers citing "Neural Ordinary Differential Equations"

50 / 822 papers shown

Title
Differentiable Molecular Simulations for Control and Learning Wujie Wang Simon Axelrod Rafael Gómez-Bombarelli AI4CE 100 49 0 27 Feb 2020
Stochasticity in Neural ODEs: An Empirical Study V. Oganesyan Alexandra Volokhova Dmitry Vetrov BDL 17 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 21 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 24 87 0 17 Feb 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 42 176 0 16 Feb 2020
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics Alexander Tong Jessie Huang Guy Wolf David van Dijk Smita Krishnaswamy 16 158 0 09 Feb 2020
Incorporating Symmetry into Deep Dynamics Models for Improved Generalization Rui Wang Robin G. Walters Rose Yu AI4CE 40 167 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 6 294 0 07 Feb 2020
Linearly Constrained Neural Networks J. Hendriks Carl Jidling A. Wills Thomas B. Schon 10 33 0 05 Feb 2020
Learning to Control PDEs with Differentiable Physics Philipp Holl V. Koltun Nils Thuerey AI4CE PINN 35 185 0 21 Jan 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 35 300 0 08 Jan 2020
Mean-Field and Kinetic Descriptions of Neural Differential Equations Michael Herty T. Trimborn G. Visconti 28 6 0 07 Jan 2020
Scalable Gradients for Stochastic Differential Equations Xuechen Li Ting-Kam Leonard Wong Ricky T. Q. Chen D. 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 24 83 0 03 Jan 2020
Machine Learning from a Continuous Viewpoint E. Weinan Chao Ma Lei Wu 21 102 0 30 Dec 2019
Discovery of Dynamics Using Linear Multistep Methods Rachael Keller Q. Du 15 36 0 29 Dec 2019
ODE-based Deep Network for MRI Reconstruction A. Yazdanpanah O. Afacan Simon K. Warfield OOD 8 3 0 27 Dec 2019
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing V. Monga Yuelong Li Yonina C. Eldar 26 996 0 22 Dec 2019
InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers T. Nguyen Animesh Garg Richard G. Baraniuk Anima Anandkumar TPM 17 9 0 09 Dec 2019
Continuous Graph Neural Networks Louis-Pascal Xhonneux Meng Qu Jian Tang GNN 19 149 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 23 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 Aurélien Lucchi 22 18 0 12 Nov 2019
Decomposable-Net: Scalable Low-Rank Compression for Neural Networks A. Yaguchi Taiji Suzuki Shuhei Nitta Y. Sakata A. Tanizawa 17 9 0 29 Oct 2019
Neural Similarity Learning Weiyang Liu Zhen Liu James M. Rehg Le Song 18 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 18 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 18 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 18 30 0 22 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 11 214 0 30 Sep 2019
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 146 219 0 29 Sep 2019
Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN 31 267 0 26 Sep 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 17 3 0 16 Aug 2019
Wasserstein Robust Reinforcement Learning Mohammed Abdullah Hang Ren Haitham Bou-Ammar Vladimir Milenkovic Rui Luo Mingtian Zhang Jun Wang 22 75 0 30 Jul 2019
Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning Peter Y. Lu Samuel Kim Marin Soljacic AI4CE 14 59 0 13 Jul 2019
Latent ODEs for Irregularly-Sampled Time Series Yulia Rubanova Ricky T. Q. Chen D. Duvenaud BDL AI4TS 27 251 0 08 Jul 2019
PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows Guandao Yang Xun Huang Zekun Hao Ming-Yu Liu Serge J. Belongie Bharath Hariharan 3DPC 13 654 0 28 Jun 2019
Neural ODEs as the Deep Limit of ResNets with constant weights B. Avelin K. Nystrom ODL 32 31 0 28 Jun 2019
Efficient and Effective Context-Based Convolutional Entropy Modeling for Image Compression Mu-Wei Li Kede Ma J. You David C. Zhang W. Zuo 22 67 0 24 Jun 2019
A Review on Deep Learning in Medical Image Reconstruction Hai-Miao Zhang Bin Dong MedIm 29 122 0 23 Jun 2019
Region-specific Diffeomorphic Metric Mapping Zhengyang Shen Franccois-Xavier Vialard Marc Niethammer 11 47 0 01 Jun 2019
Structured Output Learning with Conditional Generative Flows You Lu Bert Huang BDL DRL 11 72 0 30 May 2019
GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series E. Brouwer Jaak Simm Adam Arany Yves Moreau SyDa CML AI4TS 16 289 0 29 May 2019
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video Miguel Jaques Michael G. Burke Timothy M. Hospedales VGen PINN 21 44 0 27 May 2019
Neural Jump Stochastic Differential Equations J. Jia Austin R. Benson BDL 18 222 0 24 May 2019
Neural ODEs with stochastic vector field mixtures Niall Twomey Michał Kozłowski Raúl Santos-Rodríguez 8 4 0 23 May 2019
Enforcing constraints for time series prediction in supervised, unsupervised and reinforcement learning P. Stinis AI4TS AI4CE 18 11 0 17 May 2019