3 citations · 5 across the 4 of their papers we have counts for
5 papers
The principles of adaptation in organisms and machines II: Thermodynamics of the Bayesian brain
Hideaki Shimazaki
This article reviews how organisms learn and recognize the world through the dynamics of neural networks from the perspective of Bayesian inference, and introduces a view on how su…
Structured Mean-field Variational Inference and Learning in Winner-take-all Spiking Neural Networks
Shashwat Shukla, Hideaki Shimazaki, Udayan Ganguly
The Bayesian view of the brain hypothesizes that the brain constructs a generative model of the world, and uses it to make inferences via Bayes' rule. Although many types of approx…
The principles of adaptation in organisms and machines I: machine learning, information theory, and thermodynamics
Hideaki Shimazaki
How do organisms recognize their environment by acquiring knowledge about the world, and what actions do they take based on this knowledge? This article examines hypotheses about o…
Online Estimation of Multiple Dynamic Graphs in Pattern Sequences
Jimmy Gaudreault, Arunabh Saxena, Hideaki Shimazaki
Sequences of correlated binary patterns can represent many time-series data including text, movies, and biological signals. These patterns may be described by weighted combinations…
State-space analysis of an Ising model reveals contributions of pairwise interactions to sparseness, fluctuation, and stimulus coding of monkey V1 neurons
Jimmy Gaudreault, Hideaki Shimazaki
In this study, we analyzed the activity of monkey V1 neurons responding to grating stimuli of different orientations using inference methods for a time-dependent Ising model. The m…