Neural Ordinary Differential Equations

19 June 2018

Papers citing "Neural Ordinary Differential Equations"

50 / 948 papers shown

Title
Quasi-Taylor Samplers for Diffusion Generative Models based on Ideal Derivatives Hideyuki Tachibana Mocho Go Muneyoshi Inahara Yotaro Katayama Yotaro Watanabe DiffM 27 3 0 26 Dec 2021
Bi-Directional Recurrent Neural Ordinary Differential Equations for Social Media Text Classification Maunika Tamire Srinivas Anumasa P. K. Srijith GNN AI4TS 18 2 0 23 Dec 2021
Learning Positional Embeddings for Coordinate-MLPs Sameera Ramasinghe Simon Lucey 27 10 0 21 Dec 2021
GOPHER: Categorical probabilistic forecasting with graph structure via local continuous-time dynamics Ke Alexander Wang Danielle C. Maddix Yuyang Wang AI4CE 28 1 0 18 Dec 2021
Constraint-based graph network simulator Yulia Rubanova Alvaro Sanchez-Gonzalez Tobias Pfaff Peter W. Battaglia PINN AI4CE 32 28 0 16 Dec 2021
Distributed neural network control with dependability guarantees: a compositional port-Hamiltonian approach Luca Furieri C. Galimberti M. Zakwan Giancarlo Ferrari-Trecate 29 20 0 16 Dec 2021
AdaViT: Adaptive Tokens for Efficient Vision Transformer Hongxu Yin Arash Vahdat J. Álvarez Arun Mallya Jan Kautz Pavlo Molchanov ViT 35 314 0 14 Dec 2021
Learning High-Dimensional Parametric Maps via Reduced Basis Adaptive Residual Networks Thomas O'Leary-Roseberry Xiaosong Du A. Chaudhuri J. Martins Karen E. Willcox Omar Ghattas 30 22 0 14 Dec 2021
Generate Point Clouds with Multiscale Details from Graph-Represented Structures Ximing Yang Zhibo Zhang Zhengfu He Cheng Jin 3DPC 15 1 0 13 Dec 2021
A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis T. Lew Lucas Janson Riccardo Bonalli Marco Pavone 24 18 0 10 Dec 2021
Predicting Physical World Destinations for Commands Given to Self-Driving Cars Dusan Grujicic Thierry Deruyttere Marie-Francine Moens Matthew Blaschko OOD 24 6 0 10 Dec 2021
Safe Autonomous Navigation for Systems with Learned SE(3) Hamiltonian Dynamics Zhichao Li T. Duong Nikolay Atanasov 32 2 0 09 Dec 2021
Deep Efficient Continuous Manifold Learning for Time Series Modeling Seungwoo Jeong Wonjun Ko A. Mulyadi Heung-Il Suk AI4TS 29 8 0 03 Dec 2021
Residual Pathway Priors for Soft Equivariance Constraints Marc Finzi Gregory W. Benton A. Wilson BDL UQCV 24 50 0 02 Dec 2021
Forward Operator Estimation in Generative Models with Kernel Transfer Operators Z. Huang Rudrasis Chakraborty Vikas Singh GAN 14 3 0 01 Dec 2021
Path Integral Sampler: a stochastic control approach for sampling Qinsheng Zhang Yongxin Chen DiffM 18 101 0 30 Nov 2021
Latent Transformations via NeuralODEs for GAN-based Image Editing Valentin Khrulkov L. Mirvakhabova Ivan V. Oseledets Artem Babenko 33 14 0 29 Nov 2021
Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions Juncheng Dong Simiao Ren Yang Deng Omar Khatib Jordan M. Malof Mohammadreza Soltani Willie J. Padilla Vahid Tarokh 33 0 0 26 Nov 2021
Characteristic Neural Ordinary Differential Equations Xingzi Xu Ali Hasan Khalil Elkhalil Jie Ding Vahid Tarokh BDL 29 3 0 25 Nov 2021
An Overview of Healthcare Data Analytics With Applications to the COVID-19 Pandemic Z. Fei Y. Ryeznik O. Sverdlov C. Tan Weng Kee Wong 23 20 0 25 Nov 2021
Generalized Normalizing Flows via Markov Chains Paul Hagemann J. Hertrich Gabriele Steidl BDL DiffM AI4CE 30 22 0 24 Nov 2021
Input Convex Gradient Networks Jack Richter-Powell Jonathan Lorraine Brandon Amos 12 15 0 23 Nov 2021
Composing Partial Differential Equations with Physics-Aware Neural Networks Matthias Karlbauer T. Praditia S. Otte S. Oladyshkin Wolfgang Nowak Martin Volker Butz AI4CE 40 18 0 23 Nov 2021
NeuralPDE: Modelling Dynamical Systems from Data Andrzej Dulny Andreas Hotho Anna Krause AI4CE 24 11 0 15 Nov 2021
Climate Modeling with Neural Diffusion Equations JeeHyun Hwang Jeongwhan Choi Hwan-Kyu Choi Kookjin Lee Dongeun Lee Noseong Park DiffM 29 22 0 11 Nov 2021
Advances in Neural Rendering A. Tewari Justus Thies B. Mildenhall P. Srinivasan E. Tretschk ... S. Fanello Jun Zhu Gordon Wetzstein Michael Zollhoefer D. B. Goldman 3DH AI4CE 48 444 0 10 Nov 2021
Which priors matter? Benchmarking models for learning latent dynamics Aleksandar Botev Andrew Jaegle Peter Wirnsberger Daniel Hennes I. Higgins AI4CE 32 28 0 09 Nov 2021
A research framework for writing differentiable PDE discretizations in JAX A. Stanziola Simon Arridge B. Cox B. Treeby 26 8 0 09 Nov 2021
On Training Implicit Models Zhengyang Geng Xinyu Zhang Shaojie Bai Yisen Wang Zhouchen Lin 61 69 0 09 Nov 2021
On the Stochastic Stability of Deep Markov Models Ján Drgoňa Sayak Mukherjee Jiaxin Zhang Frank Liu M. Halappanavar BDL 22 5 0 08 Nov 2021
Data-Centric Engineering: integrating simulation, machine learning and statistics. Challenges and Opportunities Indranil Pan L. Mason Omar K. Matar AI4CE 38 45 0 07 Nov 2021
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series Daniel Kramer P. Bommer Carlo Tombolini G. Koppe Daniel Durstewitz BDL AI4TS AI4CE 25 18 0 04 Nov 2021
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling Greg Ver Steeg Aram Galstyan 41 13 0 03 Nov 2021
Constructing Neural Network-Based Models for Simulating Dynamical Systems Christian Møldrup Legaard Thomas Schranz G. Schweiger Ján Drgovna Basak Falay C. Gomes Alexandros Iosifidis M. Abkar P. Larsen PINN AI4CE 33 93 0 02 Nov 2021
Learning to Assimilate in Chaotic Dynamical Systems Michael McCabe Jed Brown AI4TS 33 10 0 01 Nov 2021
RMNet: Equivalently Removing Residual Connection from Networks Fanxu Meng Hao Cheng Jia-Xin Zhuang Ke Li Xing Sun 23 11 0 01 Nov 2021
HyperPINN: Learning parameterized differential equations with physics-informed hypernetworks Filipe de Avila Belbute-Peres Yi-fan Chen Fei Sha PINN 16 38 0 28 Oct 2021
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems Andreas Schlaginhaufen Philippe Wenk Andreas Krause Florian Dorfler 35 15 0 27 Oct 2021
Physics informed machine learning with Smoothed Particle Hydrodynamics: Hierarchy of reduced Lagrangian models of turbulence M. Woodward Yifeng Tian Criston Hyett Chris L. Fryer Daniel Livescu Mikhail Stepanov Michael Chertkov AI4CE 19 8 0 25 Oct 2021
Neural Flows: Efficient Alternative to Neural ODEs Marin Bilovs Johanna Sommer Syama Sundar Rangapuram Tim Januschowski Stephan Günnemann AI4TS 21 70 0 25 Oct 2021
Using scientific machine learning for experimental bifurcation analysis of dynamic systems S. Beregi David A.W. Barton D. Rezgui S. Neild AI4CE 35 19 0 22 Oct 2021
Sinkformers: Transformers with Doubly Stochastic Attention Michael E. Sander Pierre Ablin Mathieu Blondel Gabriel Peyré 29 76 0 22 Oct 2021
Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory T. Chen Guan-Horng Liu Evangelos A. Theodorou DiffM OT 174 164 0 21 Oct 2021
One-Shot Transfer Learning of Physics-Informed Neural Networks Shaan Desai M. Mattheakis H. Joy P. Protopapas Stephen J. Roberts PINN AI4CE 27 58 0 21 Oct 2021
Controllable and Compositional Generation with Latent-Space Energy-Based Models Weili Nie Arash Vahdat Anima Anandkumar 22 78 0 21 Oct 2021
Learning quantum dynamics with latent neural ODEs M. Choi Daniel Flam-Shepherd T. Kyaw A. Aspuru‐Guzik BDL AI4CE 32 5 0 20 Oct 2021
Solving Image PDEs with a Shallow Network Pascal Getreuer P. Milanfar Xiyang Luo 29 1 0 15 Oct 2021
Diffusion Normalizing Flow Qinsheng Zhang Yongxin Chen DiffM 26 87 0 14 Oct 2021
A Multi-scale Time-series Dataset with Benchmark for Machine Learning in Decarbonized Energy Grids Xiangtian Zheng Nan Xu Loc Trinh Dongqi Wu Tong Huang S. Sivaranjani Yan Liu Le Xie AI4CE 33 43 0 12 Oct 2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks Shuai Zhang Meng Wang Sijia Liu Pin-Yu Chen Jinjun Xiong UQCV MLT 31 13 0 12 Oct 2021