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Recurrent neural network models for working memory of continuous
  variables: activity manifolds, connectivity patterns, and dynamic codes

Recurrent neural network models for working memory of continuous variables: activity manifolds, connectivity patterns, and dynamic codes

1 November 2021
Christopher J. Cueva
A. Ardalan
M. Tsodyks
N. Qian
ArXivPDFHTML

Papers citing "Recurrent neural network models for working memory of continuous variables: activity manifolds, connectivity patterns, and dynamic codes"

6 / 6 papers shown
Title
A flexible Bayesian non-parametric mixture model reveals multiple dependencies of swap errors in visual working memory
A flexible Bayesian non-parametric mixture model reveals multiple dependencies of swap errors in visual working memory
Puria Radmard
Paul M. Bays
Máté Lengyel
20
0
0
02 May 2025
Improving World Models using Deep Supervision with Linear Probes
Improving World Models using Deep Supervision with Linear Probes
Andrii Zahorodnii
28
0
0
04 Apr 2025
How Diffusion Models Learn to Factorize and Compose
How Diffusion Models Learn to Factorize and Compose
Qiyao Liang
Ziming Liu
Mitchell Ostrow
Ila Fiete
DiffM
CoGe
33
8
0
23 Aug 2024
Back to the Continuous Attractor
Back to the Continuous Attractor
Ábel Ságodi
Guillermo Martín-Sánchez
Piotr Sokól
Il Memming Park
33
2
0
31 Jul 2024
A Population-Level Analysis of Neural Dynamics in Robust Legged Robots
A Population-Level Analysis of Neural Dynamics in Robust Legged Robots
Eugene R. Rush
Christoffer Heckman
Kaushik Jayaram
J. Humbert
34
0
0
27 Jun 2023
From Data-Fitting to Discovery: Interpreting the Neural Dynamics of
  Motor Control through Reinforcement Learning
From Data-Fitting to Discovery: Interpreting the Neural Dynamics of Motor Control through Reinforcement Learning
Eugene R. Rush
Kaushik Jayaram
J. Humbert
21
1
0
18 May 2023
1