Editorial Board for section 'Information Theory, Probability and Statistics'
- Thermodynamics Section
- Statistical Physics Section
- Information Theory, Probability and Statistics Section
- Quantum Information Section
- Multidisciplinary Applications Section
- Complexity Section
- Entropy and Biology Section
- Signal and Data Analysis Section
- Astrophysics, Cosmology, and Black Holes Section
- Time Section
- Entropy Reviews Section
- Non-equilibrium Phenomena Section
Please see the section webpage for more information on this section.
Please note that the order in which the Editors appear on this page is alphabetical, and follows the structure of the editorial board presented on the MDPI website under information for editors: editorial board responsibilities.
Members
Interests: signal processing; topological signal processing; mobile edge computing; distributed optimization
Interests: application of Monte Carlo; integral geometry and information theory techniques to radiosity; global illumination; visualization and image processing
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Interests: artificial neural networks; pattern recognition; cluster analysis; statistical learning theory; data mining; multiple classifier systems; sensor fusion; affective computing
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2. Department of Computer Science, University of Ulm, 89081 Ulm, Germany
Interests: theoretical neuroscience; memory; sensory processing; visual system; active learning; Bayesian methods; information theory
Interests: information theory; distributed intelligence; semantic communication; statistical inference
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Interests: Bayesian statistics and decision analysis; stochastic modeling; statistical aspects of reliability analysis; time series analysis
Interests: Bayesian inference; foundations of statistics; significance measures; evidence; logic and epistemology of significance measures
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Interests: machine learning and neural networks; analysis of physiological signals; complex networks theory and its applications in neurosciences
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Interests: Kullback-Leibler; large deviations; finance; economics; Esscher transform
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Interests: information and coding theory; communication networks; resource allocation; coded computing and storage; decentralized system optimization; evolutionary computation
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Interests: distributed optimization; generative AI; networks and edge learning
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Interests: wireless communications; MIMO systems; IoT networks; NOMA systems; satellite systems; information measures; channel capacity
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Interests: cognitive radios; detection and estimation; diversity and fading countermeasures; multiple-input multiple-output (MIMO) systems; multiuser communications; orthogonal frequency division multiplexing (OFDM); relay-assisted/cooperative communications
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Interests: nonlinear time series; model selection; ecology; economics; dimension reduction; entropy
Editorial Board Member
Interests: process analysis and modelling; optimal control and Pontryagin's principle; sensor fusion and vision analysis applications in electromechanical systems; synthesis and research in foundations of inference and machine learning methods; optimal resource allocation using variational programming
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Interests: probability theory; Bayesian inference; machine learning; information geometry; differential geometry; nuclear fusion; plasma physics; plasma turbulence; continuum mechanics; statistical mechanics
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Interests: 6G communications and networks including RIS and ISAC; wireless communications physical layer security; artificial intelligence driven communications
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Interests: statistical modeling and inference for data with a very complex structure and/or with high dimension
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Interests: information theory; network coding; coding theory; network communication; network computation; quantum information
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Interests: information theoretic learning; information bottleneck; deep learning; artificial general intelligence; correntropy
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Interests: information theory; communications; machine learning
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Interests: information geometry; duality in information science
Interests: causal discovery and inference; machine learning; concept learning
Interests: wireless communications; information theory; statistical inference
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Interests: learning theory; deep learning; information geometry; statistical inference; multi-terminal information theory
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