AIMC Topic: Information Theory

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Informational embodiment: Computational role of information structure in codes and robots.

Physics of life reviews Mar 21, 2025
The body morphology plays an important role in the way information is perceived and processed by an agent. We address an information theory (IT) account on how the precision of sensors, the accuracy of motors, their placement, the body geometry, shap...
Robotics Entropy Information Theory Humans
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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 Mar 18, 2025
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...
Learning Female Machine Learning Algorithms Male Neuronal Plasticity Young Adult Adult Humans Artificial Intelligence Auditory Perception Visual Perception Acoustic Stimulation Information Theory Visual Prosthesis
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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 Mar 5, 2025
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...
Neurons Memory Learning Models, Neurological Humans Information Theory Neural Networks, Computer Algorithms
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Spatial-Temporal Dynamic Hypergraph Information Bottleneck for Brain Network Classification.

International journal of neural systems Jul 17, 2024
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...
Nerve Net Information Theory Neural Networks, Computer Brain Humans
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On Information Plane Analyses of Neural Network Classifiers-A Review.

IEEE transactions on neural networks and learning systems Nov 30, 2022
We review the current literature concerned with information plane (IP) analyses of neural network (NN) classifiers. While the underlying information bottleneck theory and the claim that information-theoretic compression is causally linked to generali...
Information Theory Neural Networks, Computer Data Compression
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Understanding Neural Networks and Individual Neuron Importance via Information-Ordered Cumulative Ablation.

IEEE transactions on neural networks and learning systems Nov 30, 2022
In this work, we investigate the use of three information-theoretic quantities-entropy, mutual information with the class variable, and a class selectivity measure based on Kullback-Leibler (KL) divergence-to understand and study the behavior of alre...
Information Theory Neural Networks, Computer Neurons Entropy
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IBD: An Interpretable Backdoor-Detection Method via Multivariate Interactions.

Sensors (Basel, Switzerland) Nov 10, 2022
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 ...
Humans Neural Networks, Computer Inflammatory Bowel Diseases Information Theory
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A framework for preparing a stochastic nonlinear integrate-and-fire model for integrated information theory.

Network (Bristol, England) Apr 5, 2022
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...
Stochastic Processes Information Theory Action Potentials Neurons Reproducibility of Results Neural Networks, Computer Models, Neurological Computer Simulation
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HRel: Filter pruning based on High Relevance between activation maps and class labels.

Neural networks : the official journal of the International Neural Network Society Dec 30, 2021
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...
Neural Networks, Computer Information Theory
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Tinnitus-like "hallucinations" elicited by sensory deprivation in an entropy maximization recurrent neural network.

PLoS computational biology Dec 8, 2021
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...
Algorithms Information Theory Computer Simulation Humans Hallucinations Neuronal Plasticity Neural Networks, Computer Cochlear Nucleus Tinnitus Auditory Perception Entropy Sensory Deprivation
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