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Learning Recurrent Neural Net Models of Nonlinear Systems
v1v2v3v4 (latest)

Learning Recurrent Neural Net Models of Nonlinear Systems

Conference on Learning for Dynamics & Control (L4DC), 2020
18 November 2020
Joshua Hanson
Maxim Raginsky
Eduardo Sontag
ArXiv (abs)PDFHTML

Papers citing "Learning Recurrent Neural Net Models of Nonlinear Systems"

9 / 9 papers shown
Length independent generalization bounds for deep SSM architectures via Rademacher contraction and stability constraints
Length independent generalization bounds for deep SSM architectures via Rademacher contraction and stability constraints
Dániel Rácz
Mihaly Petreczky
Bálint Daróczy
499
1
0
30 May 2024
A finite-sample generalization bound for stable LPV systems
A finite-sample generalization bound for stable LPV systems
Daniel Racz
Martin Gonzalez
Mihaly Petreczky
András A. Benczúr
Balint Daroczy
366
0
0
16 May 2024
State-space Models with Layer-wise Nonlinearity are Universal
  Approximators with Exponential Decaying Memory
State-space Models with Layer-wise Nonlinearity are Universal Approximators with Exponential Decaying MemoryNeural Information Processing Systems (NeurIPS), 2023
Shida Wang
Beichen Xue
390
40
0
23 Sep 2023
PAC bounds of continuous Linear Parameter-Varying systems related to
  neural ODEs
PAC bounds of continuous Linear Parameter-Varying systems related to neural ODEs
Dániel Rácz
Mihaly Petreczky
Bálint Daróczy
193
0
0
07 Jul 2023
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Inverse Approximation Theory for Nonlinear Recurrent Neural NetworksInternational Conference on Learning Representations (ICLR), 2023
Shida Wang
Zhong Li
Qianxiao Li
396
10
0
30 May 2023
PAC-Bayesian bounds for learning LTI-ss systems with input from
  empirical loss
PAC-Bayesian bounds for learning LTI-ss systems with input from empirical loss
Deividas Eringis
J. Leth
Zheng-Hua Tan
R. Wisniewski
Mihaly Petreczky
255
4
0
29 Mar 2023
PAC-Bayesian-Like Error Bound for a Class of Linear Time-Invariant
  Stochastic State-Space Models
PAC-Bayesian-Like Error Bound for a Class of Linear Time-Invariant Stochastic State-Space Models
Deividas Eringis
J. Leth
Zheng-Hua Tan
Rafal Wisniewski
Mihaly Petreczky
217
1
0
30 Dec 2022
Universal Time-Uniform Trajectory Approximation for Random Dynamical
  Systems with Recurrent Neural Networks
Universal Time-Uniform Trajectory Approximation for Random Dynamical Systems with Recurrent Neural Networks
A. Bishop
213
2
0
15 Nov 2022
Realization Theory Of Recurrent Neural ODEs Using Polynomial System
  Embeddings
Realization Theory Of Recurrent Neural ODEs Using Polynomial System Embeddings
Martin Gonzalez
Thibault Defourneau
H. Hajri
Mihaly Petreczky
266
2
0
24 May 2022
1
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