University of Innsbruck

DiSCourse Seminar with Sebastian Grandis

DiSCourse - The Digital Science Seminar Series on: Data Science in Cosmology ...
IEEE

Robust Learning and Bayesian Inference of Riemannian Probabilistic Movement Primitives for Physical Human–Robot Synergic Interaction

Abstract: Although Bayesian interaction primitives exhibit strong capabilities in skill learning and reproduction for physical human–robot interactions, they require extensive demonstrations and fail ...
eLife

Virtual Brain Inference (VBI): A flexible and integrative toolkit for efficient probabilistic inference on virtual brain models

This paper presents a valuable software package, named "Virtual Brain Inference" (VBI), that enables faster and more efficient inference of parameters in dynamical system models of whole-brain ...
Frontiers

From exchangeability to rational belief: a cognitive interpretation of de Finetti’s theorem

Probabilistic reasoning is central to many theories of human cognition, yet its foundations are often presented through abstract mathematical formalisms disconnected from the logic of belief and ...
GitHub

causal-inference-k2-algorithm

Bayesian network structure learning using hybrid K2 search and hill climbing optimization. Discovers causal relationships in observational data across datasets with 8-50 variables and up to 10K ...
Frontiers

A leptin-based Bayesian inference of a pro-satiety state reflects a basal circadian rhythm in women with obesity

Leptin, primarily secreted by adipose tissue, is a critical hormone involved in regulating energy balance and food intake by inducing satiety. Although several hormones influence satiety, leptin plays ...
Scientific Research Publishing

Bayesian Inference Method for Stable Distributions ()

Stable distributions are well-known for their desirable properties and can effectively fit data with heavy tail. However, due to the lack of an explicit probability density function and finite second ...