Search Results for author: Andreas C. Schneider

Found 2 papers, 1 papers with code

A General Framework for Interpretable Neural Learning based on Local Information-Theoretic Goal Functions

no code implementations3 Jun 2023 Abdullah Makkeh, Marcel Graetz, Andreas C. Schneider, David A. Ehrlich, Viola Priesemann, Michael Wibral

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.

A Measure of the Complexity of Neural Representations based on Partial Information Decomposition

1 code implementation21 Sep 2022 David A. Ehrlich, Andreas C. Schneider, Viola Priesemann, Michael Wibral, Abdullah Makkeh

However, the specific way in which this mutual information about the classification label is distributed among the individual neurons is not well understood: While parts of it may only be obtainable from specific single neurons, other parts are carried redundantly or synergistically by multiple neurons.

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