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 (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