Forschungsbericht 2021
Data Science Foundations E-21
Leitung: Prof. Dr. habil. Nihat Ay
Institut auf TORE
Institutswebsite
Publikationen
- How morphological computation shapes integrated information in embodied agents - Article
Langer, Carlotta; Ay, Nihat
Frontiers in Psychology 12 : 716433 (2021-11-29)
Open Access Publisher DOI
- Approaching a large deviation theory for complex systems - Article
Tirnakli, Ugur; Tsallis, Constantino; Ay, Nihat
Nonlinear Dynamics 106 (3): 2537-2546 (2021-11-01)
Publisher DOI
- Towards a Canonical Divergence within Information Geometry - Article
Felice, Domenico; Ay, Nihat
Information Geometry 4: 65-130 (2021-07)
Publisher DOI
- Parametrisation Independence of the Natural Gradient in Overparametrised Systems - inProceedings
van Oostrum, Jesse; Ay, Nihat
International Conference on Geometric Science of Information (GSI 2021)
Publisher DOI
- The Information-Geometric Perspective of Compositional Data Analysis - inBook
Erb, Ionas; Ay, Nihat
In: Advances in Compositional Data Analysis, Springer, Cham: 21-43 (2021)
Publisher DOI
- Confounding ghost channels and causality: a new approach to causal information flows - Article
Ay, Nihat
Vietnam Journal of Mathematics 49 (2): 547-576 (2021-06)
Open Access Publisher DOI
- Apportionment of work among environment, body and brain of an agent - Preprint
Langer, Carlotta; Ay, Nihat
Max-Planck-Institut für Mathematik in den Naturwissenschaften (2021-03-09)
Projekte