Cover Image

Statistics of correlations in nonlinear recurrent neural networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mato, German, Rigatuso, Facundo, Torroba, Gonzalo
Format:	Preprint
Published:	2025
Subjects:	Neurons and Cognition Disordered Systems and Neural Networks Neural and Evolutionary Computing High Energy Physics - Theory Biological Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Connectivity structure and dynamics of nonlinear recurrent neural networks
by: Clark, David G., et al.
Published: (2024)

Structure of activity in multiregion recurrent neural networks
by: Clark, David G., et al.
Published: (2024)

Hierarchy of chaotic dynamics in random modular networks
by: Kuśmierz, Łukasz, et al.
Published: (2024)

Identifying the impact of local connectivity patterns on dynamics in excitatory-inhibitory networks
by: Shao, Yuxiu, et al.
Published: (2024)

Spiking mode-based neural networks
by: Lin, Zhanghan, et al.
Published: (2023)

Random neural networks match observed dimensionality of neural population recordings and motivate stronger experimental tests
by: Zhao, Zehui, et al.
Published: (2026)

Simplified derivations for high-dimensional convex learning problems
by: Clark, David G., et al.
Published: (2024)

Response time of lateral predictive coding and benefits of modular structures
by: Cai, Guanghui, et al.
Published: (2026)

Theory of coupled neuronal-synaptic dynamics
by: Clark, David G., et al.
Published: (2023)

Linear equivalence of nonlinear recurrent neural networks
by: Clark, David G.
Published: (2026)

Mean-field analysis of a neural network with stochastic STDP
by: Helson, Pascal, et al.
Published: (2025)

Learn to integrate parts for whole through correlated neural variability
by: Zhu, Zhichao, et al.
Published: (2024)

Solution of a large nonlinear recurrent neural network at fixed connectivity
by: Wakhloo, Albert J.
Published: (2026)

A Dynamical Theory of Sequential Retrieval in Input-Driven Hopfield Networks
by: Betteti, Simone, et al.
Published: (2026)

Analytically tractable model of synaptic crowding explains emergent small-world structure and network dynamics
by: Fukushima, Makoto
Published: (2026)

Dynamical stability for dense patterns in discrete attractor neural networks
by: Cohen, Uri, et al.
Published: (2025)

Toward stochastic neural computing
by: Qi, Yang, et al.
Published: (2023)

Emergence of robust memory manifolds
by: Can, Tankut, et al.
Published: (2021)

Stochastic synaptic dynamics under learning
by: Stubenrauch, Jakob, et al.
Published: (2025)

Scale-free behavior of weight distributions of connectomes
by: Cirunay, Michelle, et al.
Published: (2024)

From Chaos to Coherence: Effects of High-Order Synaptic Correlations on Neural Dynamics
by: Sherf, Nimrod, et al.
Published: (2025)

From the perceptron to the cerebellum
by: Brunel, Nicolas, et al.
Published: (2025)

Tensor formalism for predicting synaptic connections with ensemble modeling or optimization
by: Biswas, Tirthabir, et al.
Published: (2023)

Effects of synapse location, delay and background stochastic activity on synchronising hippocampal CA1 neurons
by: Fiasconaro, Alessandro, et al.
Published: (2024)

Geometric Phase Transition Enables Extreme Hippocampal Memory Capacity
by: Raju, Prashant C.
Published: (2026)

Hippocampal synchronization in a realistic CA1 neuron model
by: Fiasconaro, Alessandro, et al.
Published: (2024)

Sketch of a novel approach to a neural model
by: Scheler, Gabriele
Published: (2022)

DeepNose: An Equivariant Convolutional Neural Network Predictive Of Human Olfactory Percepts
by: Shuvaev, Sergey, et al.
Published: (2024)

Neural Langevin Machine: a local asymmetric learning rule can be creative
by: Yu, Zhendong, et al.
Published: (2025)

Signal-to-Noise Ratio and Sample Size Govern Representational Alignment in Neural Networks
by: Umar, Ali Hussaini, et al.
Published: (2026)

Freezing chaos without synaptic plasticity
by: Huang, Weizhong, et al.
Published: (2025)

Nonlinear classification of neural manifolds with contextual information
by: Mignacco, Francesca, et al.
Published: (2024)

Neuronal correlations shape the scaling behavior of memory capacity and nonlinear computational capability of reservoir recurrent neural networks
by: Takasu, Shotaro, et al.
Published: (2025)

Chaotic synchronization in adaptive networks of pulse-coupled oscillators
by: Mato, German, et al.
Published: (2024)

Slow Transition to Low-Dimensional Chaos in Heavy-Tailed Recurrent Neural Networks
by: Xie, Yi, et al.
Published: (2025)

Modeling Bioelectric State Transitions in Glial Cells: An ASAL-Inspired Computational Approach to Glioblastoma Initiation
by: Pawlak, Wiktoria Agata
Published: (2025)

Random matrix theory of sparse neuronal networks with heterogeneous timescales
by: Chotibut, Thiparat, et al.
Published: (2025)

Statistical mechanics for networks of real neurons
by: Meshulam, Leenoy, et al.
Published: (2024)

A robust balancing mechanism for spiking neural networks
by: Politi, Antonio, et al.
Published: (2024)

Applications of information geometry to spiking neural network behavior
by: Crosser, Jacob T., et al.
Published: (2023)