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Reverse engineering recurrent neural networks with Jacobian switching
  linear dynamical systems

Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems

1 November 2021
Jimmy T.H. Smith
Scott W. Linderman
David Sussillo
ArXivPDFHTML

Papers citing "Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems"

13 / 13 papers shown
Title
Modeling Neural Activity with Conditionally Linear Dynamical Systems
Modeling Neural Activity with Conditionally Linear Dynamical Systems
Victor Geadah
Amin Nejatbakhsh
David Lipshutz
Jonathan W. Pillow
Alex H. Williams
AI4CE
43
0
0
25 Feb 2025
Towards Scalable and Stable Parallelization of Nonlinear RNNs
Towards Scalable and Stable Parallelization of Nonlinear RNNs
Xavier Gonzalez
Andrew Warrington
Jimmy T.H. Smith
Scott W. Linderman
93
8
0
17 Jan 2025
Self-supervised contrastive learning performs non-linear system
  identification
Self-supervised contrastive learning performs non-linear system identification
Rodrigo González Laiz
Tobias Schmidt
Steffen Schneider
SSL
39
0
0
18 Oct 2024
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems
Amber Hu
D. Zoltowski
Aditya Nair
David Anderson
Lea Duncker
Scott W. Linderman
36
3
0
19 Jul 2024
DFORM: Diffeomorphic vector field alignment for assessing dynamics
  across learned models
DFORM: Diffeomorphic vector field alignment for assessing dynamics across learned models
Ruiqi Chen
Giacomo Vedovati
Todd S. Braver
ShiNung Ching
19
1
0
15 Feb 2024
Generative learning for nonlinear dynamics
Generative learning for nonlinear dynamics
William Gilpin
AI4CE
PINN
60
24
0
07 Nov 2023
Bifurcations and loss jumps in RNN training
Bifurcations and loss jumps in RNN training
Lukas Eisenmann
Zahra Monfared
Niclas Alexander Göring
Daniel Durstewitz
19
8
0
26 Oct 2023
On the Dynamics of Learning Time-Aware Behavior with Recurrent Neural
  Networks
On the Dynamics of Learning Time-Aware Behavior with Recurrent Neural Networks
Peter DelMastro
Rushiv Arora
E. Rietman
H. Siegelmann
AI4TS
AI4CE
9
2
0
12 Jun 2023
Generalized Teacher Forcing for Learning Chaotic Dynamics
Generalized Teacher Forcing for Learning Chaotic Dynamics
Florian Hess
Zahra Monfared
Manuela Brenner
Daniel Durstewitz
AI4CE
27
30
0
07 Jun 2023
Expressive architectures enhance interpretability of dynamics-based
  neural population models
Expressive architectures enhance interpretability of dynamics-based neural population models
Andrew R. Sedler
Chris VerSteeg
C. Pandarinath
34
10
0
07 Dec 2022
Beyond accuracy: generalization properties of bio-plausible temporal
  credit assignment rules
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules
Yuhan Helena Liu
Arna Ghosh
Blake A. Richards
E. Shea-Brown
Guillaume Lajoie
31
9
0
02 Jun 2022
Neural Latents Benchmark '21: Evaluating latent variable models of
  neural population activity
Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity
Felix Pei
Joel Ye
D. Zoltowski
Anqi Wu
Raeed H. Chowdhury
...
L. Miller
Jonathan W. Pillow
Il Memming Park
Eva L. Dyer
C. Pandarinath
50
86
0
09 Sep 2021
Fourier Neural Operator for Parametric Partial Differential Equations
Fourier Neural Operator for Parametric Partial Differential Equations
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
232
2,287
0
18 Oct 2020
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