Neural Ordinary Differential Equations

19 June 2018

Papers citing "Neural Ordinary Differential Equations"

50 / 1,087 papers shown

Title
Continuous Graph Neural Networks Louis-Pascal Xhonneux Meng Qu Jian Tang GNN 27 150 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 51 154 0 18 Nov 2019
Shadowing Properties of Optimization Algorithms Antonio Orvieto Aurelien Lucchi 36 18 0 12 Nov 2019
Physics-Informed Neural Networks for Power Systems George S. Misyris Andreas Venzke Spyros Chatzivasileiadis PINN AI4CE 28 213 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 22 36 0 23 Oct 2019
Machine learning and serving of discrete field theories -- when artificial intelligence meets the discrete universe H. Qin 32 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
Powering Hidden Markov Model by Neural Network based Generative Models Dong Liu Antoine Honoré S. Chatterjee L. Rasmussen BDL 13 15 0 13 Oct 2019
On Robustness of Neural Ordinary Differential Equations Hanshu Yan Jiawei Du Vincent Y. F. Tan Jiashi Feng OOD 24 138 0 12 Oct 2019
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 43 2,035 0 08 Oct 2019
Hamiltonian Generative Networks Peter Toth Danilo Jimenez Rezende Andrew Jaegle S. Racanière Aleksandar Botev I. Higgins BDL DRL AI4CE GAN 21 216 0 30 Sep 2019
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 152 221 0 29 Sep 2019
Hamiltonian Graph Networks with ODE Integrators Alvaro Sanchez-Gonzalez V. Bapst Kyle Cranmer Peter W. Battaglia AI4CE 31 177 0 27 Sep 2019
Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN 54 269 0 26 Sep 2019
Mean-field Langevin System, Optimal Control and Deep Neural Networks Kaitong Hu A. Kazeykina Zhenjie Ren 6 15 0 16 Sep 2019
Potential Flow Generator with $L_2$ Optimal Transport Regularity for Generative Models Liu Yang George Karniadakis OT 11 42 0 29 Aug 2019
Neural Dynamics on Complex Networks Chengxi Zang Fei Wang AI4CE 35 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 24 3 0 16 Aug 2019
Unconstrained Monotonic Neural Networks Antoine Wehenkel Gilles Louppe TPM 34 146 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
MadMiner: Machine learning-based inference for particle physics Johann Brehmer F. Kling Irina Espejo Kyle Cranmer 21 113 0 24 Jul 2019
Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning Peter Y. Lu Samuel Kim Marin Soljacic AI4CE 22 59 0 13 Jul 2019
Latent ODEs for Irregularly-Sampled Time Series Yulia Rubanova Ricky T. Q. Chen David Duvenaud BDL AI4TS 31 252 0 08 Jul 2019
PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows Guandao Yang Xun Huang Jinwei Gu Ming Liu Serge J. Belongie Bharath Hariharan 3DPC 40 660 0 28 Jun 2019
Neural ODEs as the Deep Limit of ResNets with constant weights B. Avelin K. Nystrom ODL 40 31 0 28 Jun 2019
Perceptual Generative Autoencoders Zijun Zhang Ruixiang Zhang Zongpeng Li Yoshua Bengio Liam Paull DRL GAN 25 28 0 25 Jun 2019
Efficient and Effective Context-Based Convolutional Entropy Modeling for Image Compression Mu Li Kede Ma J. You David C. Zhang W. Zuo 30 67 0 24 Jun 2019
A Review on Deep Learning in Medical Image Reconstruction Hai-Miao Zhang Bin Dong MedIm 35 122 0 23 Jun 2019
SNODE: Spectral Discretization of Neural ODEs for System Identification A. Quaglino Marco Gallieri Jonathan Masci Jan Koutník AI4TS 21 48 0 17 Jun 2019
Normalizing flows for novelty detection in industrial time series data Maximilian Schmidt M. Šimic DRL AI4TS AI4CE 27 25 0 17 Jun 2019
Tackling Climate Change with Machine Learning David Rolnick P. Donti L. Kaack K. Kochanski Alexandre Lacoste ... Demis Hassabis John C. Platt F. Creutzig J. Chayes Yoshua Bengio AI4Cl AI4CE 38 788 0 10 Jun 2019
Neural Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios DRL 41 748 0 10 Jun 2019
ANODEV2: A Coupled Neural ODE Evolution Framework Tianjun Zhang Z. Yao A. Gholami Kurt Keutzer Joseph E. Gonzalez George Biros Michael W. Mahoney 22 41 0 10 Jun 2019
Cubic-Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios TPM 53 57 0 05 Jun 2019
Region-specific Diffeomorphic Metric Mapping Zhengyang Shen Franccois-Xavier Vialard Marc Niethammer 16 47 0 01 Jun 2019
Greedy inference with structure-exploiting lazy maps Michael C. Brennan Daniele Bigoni O. Zahm Alessio Spantini Youssef Marzouk 22 13 0 31 May 2019
Structured Output Learning with Conditional Generative Flows You Lu Bert Huang BDL DRL 21 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 45 290 0 29 May 2019
Differentiable Algorithm Networks for Composable Robot Learning Peter Karkus Xiao Ma David Hsu L. Kaelbling Wee Sun Lee Tomas Lozano-Perez 22 70 0 28 May 2019
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video Miguel Jaques Michael G. Burke Timothy M. Hospedales VGen PINN 21 45 0 27 May 2019
Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning Yufei Wang Ziju Shen Zichao Long Bin Dong AI4CE PINN 13 40 0 27 May 2019
Infinitely deep neural networks as diffusion processes Stefano Peluchetti Stefano Favaro ODL 16 31 0 27 May 2019
ODE $^2$ VAE: Deep generative second order ODEs with Bayesian neural networks Çağatay Yıldız Markus Heinonen Harri Lähdesmäki BDL DRL 27 88 0 27 May 2019
Neural Jump Stochastic Differential Equations Junteng Jia Austin R. Benson BDL 20 222 0 24 May 2019