Cover Image

Neural Langevin Machine: a local asymmetric learning rule can be creative

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yu, Zhendong, Huang, Weizhong, Huang, Haiping
Format:	Preprint
Published:	2025
Subjects:	Neurons and Cognition Disordered Systems and Neural Networks Machine Learning Neural and Evolutionary Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Fermi-Bose Machine achieves both generalization and adversarial robustness
by: Xie, Mingshan, et al.
Published: (2024)

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

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

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

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

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

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

Differential learning kinetics govern the transition from memorization to generalization during in-context learning
by: Nguyen, Alex, et al.
Published: (2024)

Heterosynaptic Circuits Are Universal Gradient Machines
by: Ziyin, Liu, et al.
Published: (2025)

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

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

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

Neural population geometry and optimal coding of tasks with shared latent structure
by: Wakhloo, Albert J., et al.
Published: (2024)

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

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

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)

Introduction to dynamical mean-field theory of randomly connected neural networks with bidirectionally correlated couplings
by: Zou, Wenxuan, et al.
Published: (2023)

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

Self-supervised local learning rules learn the hidden hierarchical structure of high-dimensional data
by: Delrocq, Ariane, et al.
Published: (2026)

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

Learning in Wilson-Cowan model for metapopulation
by: Marino, Raffaele, et al.
Published: (2024)

Dynamically Learning to Integrate in Recurrent Neural Networks
by: Bordelon, Blake, et al.
Published: (2025)

Dynamical Learning in Deep Asymmetric Recurrent Neural Networks
by: Badalotti, Davide, et al.
Published: (2025)

Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks
by: Mannelli, Stefano Sarao, et al.
Published: (2024)

Synaptic plasticity alters the nature of chaos transition in neural networks
by: Du, Wenkang, et al.
Published: (2024)

When can in-context learning generalize out of task distribution?
by: Goddard, Chase, et al.
Published: (2025)

Network reconstruction may not mean dynamics prediction
by: Yu, Zhendong, et al.
Published: (2024)

Meta-learning three-factor plasticity rules for structured credit assignment with sparse feedback
by: Maoutsa, Dimitra
Published: (2025)

Finite integration time can shift optimal sensitivity away from criticality
by: Azizpour, Sahel, et al.
Published: (2026)

Proof of a perfect platonic representation hypothesis
by: Ziyin, Liu, et al.
Published: (2025)

Responses to transient perturbation can distinguish intrinsic from latent criticality in spiking neural populations
by: Crosser, Jacob T., et al.
Published: (2025)

Energy--Information Trade-off Induces Continuous and Discontinuous Phase Transitions in Lateral Predictive Coding
by: Huang, Zhen-Ye, et al.
Published: (2023)

Mitigating Communication Costs in Neural Networks: The Role of Dendritic Nonlinearity
by: Wu, Xundong, et al.
Published: (2023)

Spectral Analysis of Representational Similarity with Limited Neurons
by: Kang, Hyunmo, et al.
Published: (2025)

Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge Ensembles
by: Ruben, Benjamin S., et al.
Published: (2023)

L1-Regularized ICA: A Novel Method for Analysis of Task-related fMRI Data
by: Endo, Yusuke, et al.
Published: (2024)

Statistical Mechanics of Support Vector Regression
by: Canatar, Abdulkadir, 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)