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Information Theory

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Explainable Molecular Sets: Using Information Theory to Generate Meaningful Descriptions of Groups of Molecules.

Journal of chemical information and modeling
Algorithmically identifying the meaningful similarities between an assortment of molecules is a critical chemical problem, and one which is only gaining in relevance as data-driven chemistry continues to progress. Effectively addressing this challeng...

The information theory of developmental pruning: Optimizing global network architectures using local synaptic rules.

PLoS computational biology
During development, biological neural networks produce more synapses and neurons than needed. Many of these synapses and neurons are later removed in a process known as neural pruning. Why networks should initially be over-populated, and the processe...

HRel: Filter pruning based on High Relevance between activation maps and class labels.

Neural networks : the official journal of the International Neural Network Society
This paper proposes an Information Bottleneck theory based filter pruning method that uses a statistical measure called Mutual Information (MI). The MI between filters and class labels, also called Relevance, is computed using the filter's activation...

Tinnitus-like "hallucinations" elicited by sensory deprivation in an entropy maximization recurrent neural network.

PLoS computational biology
Sensory deprivation has long been known to cause hallucinations or "phantom" sensations, the most common of which is tinnitus induced by hearing loss, affecting 10-20% of the population. An observable hearing loss, causing auditory sensory deprivatio...

Application of information theoretic feature selection and machine learning methods for the development of genetic risk prediction models.

Scientific reports
In view of the growth of clinical risk prediction models using genetic data, there is an increasing need for studies that use appropriate methods to select the optimum number of features from a large number of genetic variants with a high degree of r...

A framework for preparing a stochastic nonlinear integrate-and-fire model for integrated information theory.

Network (Bristol, England)
This paper presents a framework for spiking neural networks to be prepared for the Integrated Information Theory (IIT) analysis, using a stochastic nonlinear integrate-and-fire model. The model includes the crucial dynamics of the all-or-none law and...

IBD: An Interpretable Backdoor-Detection Method via Multivariate Interactions.

Sensors (Basel, Switzerland)
Recent work has shown that deep neural networks are vulnerable to backdoor attacks. In comparison with the success of backdoor-attack methods, existing backdoor-defense methods face a lack of theoretical foundations and interpretable solutions. Most ...

Spatial-Temporal Dynamic Hypergraph Information Bottleneck for Brain Network Classification.

International journal of neural systems
Recently, Graph Neural Networks (GNNs) have gained widespread application in automatic brain network classification tasks, owing to their ability to directly capture crucial information in non-Euclidean structures. However, two primary challenges per...

Improving Acceptance to Sensory Substitution: A Study on the V2A-SS Learning Model Based on Information Processing Learning Theory.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The visual sensory organ (VSO) serves as the primary channel for transmitting external information to the brain; therefore, damage to the VSO can severely limit daily activities. Visual-to-Auditory Sensory Substitution (V2A-SS), an innovative approac...

A general framework for interpretable neural learning based on local information-theoretic goal functions.

Proceedings of the National Academy of Sciences of the United States of America
Despite the impressive performance of biological and artificial networks, an intuitive understanding of how their local learning dynamics contribute to network-level task solutions remains a challenge to this date. Efforts to bring learning to a more...