Shaping Dynamics With Multiple Populations in Low-Rank Recurrent Networks

DOI10.1162/NECO_A_01381zbMath1469.92014arXiv2007.02062OpenAlexW3155593980MaRDI QIDQ5004376

Manuel Beiran, Srdjan Ostojic, Francesca Mastrogiuseppe, Adrian Valente, Alexis M. Dubreuil

Publication date: 30 July 2021

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2007.02062

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20)

Related Items (3)

Probing the Relationship Between Latent Linear Dynamical Systems and Low-Rank Recurrent Neural Network Models ⋮ Bifurcations of a Neural Network Model with Symmetry ⋮ STDP-based associative memory formation and retrieval

Cites Work

• Multilayer feedforward networks are universal approximators
• Universal approximation with quadratic deep networks
• Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations
• A Unified Approach to Building and Controlling Spiking Attractor Networks
• A Geometrical Analysis of Global Stability in Trained Feedback Networks
• Neural networks and physical systems with emergent collective computational abilities.
• Approximation by superpositions of a sigmoidal function

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