Augmented Neural ODEs

2 April 2019

Papers citing "Augmented Neural ODEs"

25 / 25 papers shown

Title
Uncertainty quantification of neural network models of evolving processes via Langevin sampling Cosmin Safta Reese E. Jones Ravi G. Patel Raelynn Wonnacot Dan S. Bolintineanu Craig M. Hamel S. Kramer BDL 67 0 0 21 Apr 2025
"Only ChatGPT gets me": An Empirical Analysis of GPT versus other Large Language Models for Emotion Detection in Text Florian Lecourt Madalina Croitoru Konstantin Todorov AI4MH 53 0 0 05 Mar 2025
Learning to Decouple Complex Systems Zihan Zhou Tianshu Yu BDL 95 4 0 17 Feb 2025
Learning Memory and Material Dependent Constitutive Laws K. Bhattacharya Lianghao Cao George Stepaniants Andrew M. Stuart Margaret Trautner 90 1 0 08 Feb 2025
Trajectory Flow Matching with Applications to Clinical Time Series Modeling Xi Zhang Yuan Pu Yuki Kawamura Andrew Loza Yoshua Bengio Dennis L. Shung Alexander Tong OOD AI4TS MedIm 55 5 0 28 Oct 2024
Score-based Neural Ordinary Differential Equations for Computing Mean Field Control Problems Mo Zhou Stanley Osher Wuchen Li 98 4 0 24 Sep 2024
Neural Differential Appearance Equations Chen Liu Tobias Ritschel 45 0 0 23 Sep 2024
Neural CRNs: A Natural Implementation of Learning in Chemical Reaction Networks Rajiv Teja Nagipogu John H. Reif 49 0 0 18 Aug 2024
Beyond Predictions in Neural ODEs: Identification and Interventions H. Aliee Fabian J. Theis Niki Kilbertus CML 71 24 0 23 Jun 2021
Large-time asymptotics in deep learning Carlos Esteve Borjan Geshkovski Dario Pighin Enrique Zuazua 54 34 0 06 Aug 2020
ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust Accuracies Bao Wang Binjie Yuan Zuoqiang Shi Stanley J. Osher AAML OOD 26 15 0 26 Nov 2018
Invertible Residual Networks Jens Behrmann Will Grathwohl Ricky T. Q. Chen David Duvenaud J. Jacobsen UQCV TPM 71 621 0 02 Nov 2018
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models Will Grathwohl Ricky T. Q. Chen J. Bettencourt Ilya Sutskever David Duvenaud DRL 46 861 0 02 Oct 2018
Analyzing Inverse Problems with Invertible Neural Networks Lynton Ardizzone Jakob Kruse Sebastian J. Wirkert D. Rahner E. Pellegrini R. Klessen Lena Maier-Hein Carsten Rother Ullrich Kothe 40 489 0 14 Aug 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 194 3,110 0 09 Jul 2018
ResNet with one-neuron hidden layers is a Universal Approximator Hongzhou Lin Stefanie Jegelka 62 227 0 28 Jun 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 201 5,024 0 19 Jun 2018
Deep Neural Networks Motivated by Partial Differential Equations Lars Ruthotto E. Haber AI4CE 55 488 0 12 Apr 2018
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations Yiping Lu Aoxiao Zhong Quanzheng Li Bin Dong 126 495 0 27 Oct 2017
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 116 1,340 0 19 May 2017
Stable Architectures for Deep Neural Networks E. Haber Lars Ruthotto 62 722 0 09 May 2017
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Zhuowen Tu Kaiming He 411 10,281 0 16 Nov 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 168 3,670 0 26 May 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 231 7,951 0 23 May 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.2K 192,638 0 10 Dec 2015