Entropy Special Issue : Formal Analysis of Deep Artificial Neural Networks
Dear Researchers, The Entropy Journal (https://www.mdpi.com/journal/entropy) is currently running a Special Isuue on Formal Analysis of Deep Artificial Neural Networks <https://www.mdpi.com/journal/entropy/special_issues/DANN> (Deadline: *31 May 2022) *This Special Issue welcomes original research papers on the analysis of ANNs based on mathematically founded methods in general. Review articles describing the current state of the art of ANNs in the aforementioned contexts are highly encouraged. All submissions to this Special Issue must include substantial theoretical aspects of ANN research.* * Keywords * ANN architectures and learning in approximation and complexity theories * Cost functions and constraints in information-theoretic learning algorithms for ANNs * Complexity of deep, recurrent, or quantum ANN learning * Information-theoretic principles for sampling and feature extraction * Analysis of learning based on information-theoretic methods (e.g., information bottleneck approach) in deep, recurrent, or quantum ANNs * Applications of ANNs based on information-theoretic principles or quantum computing * Theoretical advances in quantum ANNs Please contact us: Edmondo Trentin <trentin@dii.unisi.it> or Friedhelm Schwenker <friedhelm.schwenker@uni-ulm.de> if you are interested in submitting your work. A number of waivers / discounts is available for interested authors. Best wishes, Friedhelm Schwenker Edmondo Trentin -- Prof. Dr. Friedhelm Schwenker University of Ulm Institute of Neural Information Processing D-89069 Ulm, Germany phone: +49-731-50-24159 fax: +49-731-50-24156 email:friedhelm.schwenker@uni-ulm.de www:http://www.uni-ulm.de/in/neuroinformatik/mitarbeiter/f-schwenker.html
participants (1)
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Friedhelm Schwenker