Objective and efficient inference for couplings in neuronal network

DOI10.1088/1742-5468/ab3219zbMath1459.92010arXiv1805.07061OpenAlexW2803805198MaRDI QIDQ5854111

Yoshiyuki Kabashima, Yu Terada, Tomoyuki Obuchi, Takuya Isomura

Publication date: 16 March 2021

Published in: Journal of Statistical Mechanics: Theory and Experiment (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1805.07061

Mathematics Subject Classification ID

Neural biology (92C20) Neural networks for/in biological studies, artificial life and related topics (92B20) Neural nets and related approaches to inference from stochastic processes (62M45)

Uses Software

• ElemStatLearn

Cites Work

• Learning probabilities from random observables in high dimensions: the maximum entropy distribution and others
• The effect of nonstationarity on models inferred from neural data
• Small-correlation expansions for the inverse Ising problem

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