Rademacher Complexity of Neural ODEs via Chen-Fliess Series

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Rademacher Complexity of Neural ODEs via Chen-Fliess Series

30 January 2024

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Papers citing "Rademacher Complexity of Neural ODEs via Chen-Fliess Series"

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Title
Length independent generalization bounds for deep SSM architectures via Rademacher contraction and stability constraints Dániel Rácz Mihaly Petreczky Bálint Daróczy 106 1 0 30 May 2024
New directions in the applications of rough path theory Adeline Fermanian Terry Lyons James Morrill C. Salvi 129 16 0 09 Feb 2023
Framing RNN as a kernel method: A neural ODE approach Adeline Fermanian Pierre Marion Jean-Philippe Vert Gérard Biau 73 26 0 02 Jun 2021
Continuous-in-Depth Neural Networks A. Queiruga N. Benjamin Erichson D. Taylor Michael W. Mahoney 76 48 0 05 Aug 2020
Learning Differential Equations that are Easy to Solve Jacob Kelly J. Bettencourt Matthew J. Johnson David Duvenaud 91 116 0 09 Jul 2020
Neural Controlled Differential Equations for Irregular Time Series Patrick Kidger James Morrill James Foster Terry Lyons AI4TS 111 481 0 18 May 2020
Dissecting Neural ODEs Stefano Massaroli Michael Poli Jinkyoo Park Atsushi Yamashita Hajime Asama 99 204 0 19 Feb 2020
Infinitely deep neural networks as diffusion processes Stefano Peluchetti Stefano Favaro ODL 82 32 0 27 May 2019
Neural Jump Stochastic Differential Equations Junteng Jia Austin R. Benson BDL 68 229 0 24 May 2019
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 437 5,157 0 19 Jun 2018

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