Neural Ordinary Differential Equations

19 June 2018

Papers citing "Neural Ordinary Differential Equations"

50 / 947 papers shown

Title
Heavy Ball Neural Ordinary Differential Equations Hedi Xia Vai Suliafu H. Ji T. Nguyen Andrea L. Bertozzi Stanley J. Osher Bao Wang 35 56 0 10 Oct 2021
Score-based diffusion models for accelerated MRI Hyungjin Chung Jong Chul Ye DiffM MedIm 45 400 0 08 Oct 2021
Moment evolution equations and moment matching for stochastic image EPDiff Alexander Mangulad Christgau Alexis Arnaudon Stefan Sommer 18 0 0 07 Oct 2021
Scaling Up Machine Learning For Quantum Field Theory with Equivariant Continuous Flows P. D. Haan Corrado Rainone Miranda C. N. Cheng Roberto Bondesan AI4CE 11 35 0 06 Oct 2021
Score-Based Generative Classifiers Roland S. Zimmermann Lukas Schott Yang Song Benjamin A. Dunn David A. Klindt DiffM 22 64 0 01 Oct 2021
Extended dynamic mode decomposition with dictionary learning using neural ordinary differential equations H. Terao Sho Shirasaka Hideyuki Suzuki 20 6 0 01 Oct 2021
slimTrain -- A Stochastic Approximation Method for Training Separable Deep Neural Networks Elizabeth Newman Julianne Chung Matthias Chung Lars Ruthotto 47 6 0 28 Sep 2021
Physics-Augmented Learning: A New Paradigm Beyond Physics-Informed Learning Ziming Liu Yunyue Chen Yuanqi Du Max Tegmark PINN AI4CE 40 22 0 28 Sep 2021
Approximate Latent Force Model Inference Jacob Moss Felix L. Opolka Bianca Dumitrascu Pietro Lió 46 3 0 24 Sep 2021
A Latent Restoring Force Approach to Nonlinear System Identification T. Rogers Tobias Friis 21 18 0 22 Sep 2021
An Optimal Control Framework for Joint-channel Parallel MRI Reconstruction without Coil Sensitivities Wanyu Bian Yunmei Chen X. Ye 44 14 0 20 Sep 2021
Locally-symplectic neural networks for learning volume-preserving dynamics J. Bajārs 34 9 0 19 Sep 2021
PluGeN: Multi-Label Conditional Generation From Pre-Trained Models Maciej Wołczyk Magdalena Proszewska Lukasz Maziarka Maciej Ziȩba Patryk Wielopolski Rafał Kurczab Marek Śmieja DRL 27 5 0 18 Sep 2021
On the regularized risk of distributionally robust learning over deep neural networks Camilo A. Garcia Trillos Nicolas García Trillos OOD 42 10 0 13 Sep 2021
Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling Kookjin Lee Nathaniel Trask P. Stinis 35 25 0 11 Sep 2021
Hybrid modeling of the human cardiovascular system using NeuralFMUs Tobias Thummerer Johannes Tintenherr Lars Mikelsons AI4CE 21 5 0 10 Sep 2021
KNODE-MPC: A Knowledge-based Data-driven Predictive Control Framework for Aerial Robots K. Y. Chee Tom Z. Jiahao M. A. Hsieh 27 63 0 10 Sep 2021
Modeling Systems with Machine Learning based Differential Equations P. García OOD 16 1 0 09 Sep 2021
NeuralFMU: Towards Structural Integration of FMUs into Neural Networks Tobias Thummerer Josef Kircher Lars Mikelsons AI4CE 15 8 0 09 Sep 2021
DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks Christian Moya Guang Lin AI4CE PINN 56 37 0 09 Sep 2021
Simple Video Generation using Neural ODEs David Kanaa Vikram S. Voleti Samira Ebrahimi Kahou Christopher Pal 27 20 0 07 Sep 2021
Attentive Neural Controlled Differential Equations for Time-series Classification and Forecasting Sheo Yon Jhin H. Shin Seoyoung Hong Solhee Park Noseong Park AI4TS 27 22 0 04 Sep 2021
Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations Ido Ben-Yair Gil Ben Shalom Moshe Eliasof Eran Treister MQ 24 5 0 31 Aug 2021
Data-Driven Reduced-Order Modeling of Spatiotemporal Chaos with Neural Ordinary Differential Equations Alec J. Linot M. Graham 14 48 0 31 Aug 2021
Deep Generative Modeling for Protein Design Alexey Strokach Philip M. Kim AI4CE 179 90 0 31 Aug 2021
Extracting Stochastic Governing Laws by Nonlocal Kramers-Moyal Formulas Yubin Lu Yang Li Jinqiao Duan 13 16 0 28 Aug 2021
Modeling the effect of the vaccination campaign on the Covid-19 pandemic M. Angeli Georgios Neofotistos M. Mattheakis E. Kaxiras 27 37 0 27 Aug 2021
Bilateral Denoising Diffusion Models Max W. Y. Lam Jun Wang Rongjie Huang Dan Su Dong Yu DiffM 27 42 0 26 Aug 2021
Moser Flow: Divergence-based Generative Modeling on Manifolds N. Rozen Aditya Grover Maximilian Nickel Y. Lipman DRL AI4CE 27 57 0 18 Aug 2021
Verifying Low-dimensional Input Neural Networks via Input Quantization Kai Jia Martin Rinard AAML 30 13 0 18 Aug 2021
m-RevNet: Deep Reversible Neural Networks with Momentum Duo Li Shangqi Gao 16 5 0 12 Aug 2021
LightMove: A Lightweight Next-POI Recommendation for Taxicab Rooftop Advertising Jinsung Jeon Soyoung Kang Minju Jo Seunghyeon Cho Noseong Park Seonghoon Kim Chiyoung Song 28 16 0 11 Aug 2021
Deep Learning Based Antenna-time Domain Channel Extrapolation for Hybrid mmWave Massive MIMO Shun Zhang Shun Zhang Jianpeng Ma Tian Liu O. Dobre 14 7 0 09 Aug 2021
LT-OCF: Learnable-Time ODE-based Collaborative Filtering Jeongwhan Choi Jinsung Jeon Noseong Park 32 30 0 08 Aug 2021
PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations Moshe Eliasof E. Haber Eran Treister GNN AI4CE 39 122 0 04 Aug 2021
Interpreting diffusion score matching using normalizing flow Wenbo Gong Yingzhen Li DiffM 27 13 0 21 Jul 2021
GoTube: Scalable Stochastic Verification of Continuous-Depth Models Sophie Gruenbacher Mathias Lechner Ramin Hasani Daniela Rus T. Henzinger S. Smolka Radu Grosu 26 17 0 18 Jul 2021
STRODE: Stochastic Boundary Ordinary Differential Equation Hengguan Huang Hongfu Liu Hao Wang Chang Xiao Ye Wang SyDa AI4TS 24 6 0 17 Jul 2021
Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems Shaan Desai M. Mattheakis David Sondak P. Protopapas Stephen J. Roberts AI4CE 30 43 0 16 Jul 2021
Conformer-based End-to-end Speech Recognition With Rotary Position Embedding Shengqiang Li Menglong Xu Xiao-Lei Zhang 18 9 0 13 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 39 65 0 02 Jul 2021
ResIST: Layer-Wise Decomposition of ResNets for Distributed Training Chen Dun Cameron R. Wolfe C. Jermaine Anastasios Kyrillidis 16 21 0 02 Jul 2021
The Values Encoded in Machine Learning Research Abeba Birhane Pratyusha Kalluri Dallas Card William Agnew Ravit Dotan Michelle Bao 27 274 0 29 Jun 2021
Pruning Edges and Gradients to Learn Hypergraphs from Larger Sets David W. Zhang Gertjan J. Burghouts Cees G. M. Snoek 37 4 0 26 Jun 2021
Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting Zheng Fang Qingqing Long Guojie Song Kunqing Xie AI4TS 17 456 0 24 Jun 2021
Neural ODE to model and prognose thermoacoustic instability Jayesh M. Dhadphale Vishnu R Unni A. Saha R. Sujith 20 13 0 24 Jun 2021
Sparse Flows: Pruning Continuous-depth Models Lucas Liebenwein Ramin Hasani Alexander Amini Daniela Rus 26 16 0 24 Jun 2021
Machine learning structure preserving brackets for forecasting irreversible processes Kookjin Lee Nathaniel Trask P. Stinis AI4CE 44 42 0 23 Jun 2021
Beyond Predictions in Neural ODEs: Identification and Interventions H. Aliee Fabian J. Theis Niki Kilbertus CML 40 24 0 23 Jun 2021
Symplectic Learning for Hamiltonian Neural Networks M. David Florian Méhats 24 35 0 22 Jun 2021