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Found 8 papers, 2 papers with code
Information maximization for a broad variety of multi-armed bandit games
Information and free-energy maximization are physics principles that provide general rules for an agent to optimize actions in line with specific goals and policies.
Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results
The FeTA Challenge 2022 was able to successfully evaluate and advance generalizability of multi-class fetal brain tissue segmentation algorithms for MRI and it continues to benchmark new algorithms.
Compression-based inference of network motif sets
The statistical inference of network motifs is however fraught with difficulties, from defining and sampling the right null model to accounting for the large number of possible motifs and their potential correlations in statistical testing.
Approximate information maximization for bandit games
Built on this principle, we propose a new class of bandit algorithms that maximize an approximation to the information of a key variable within the system.
Approximate information for efficient exploration-exploitation strategies
This paper addresses the exploration-exploitation dilemma inherent in decision-making, focusing on multi-armed bandit problems.
Variational inference of fractional Brownian motion with linear computational complexity
Our approach learns the posterior distribution of the walks' parameters with a likelihood-free method.
Learning physical properties of anomalous random walks using graph neural networks
Here, we introduce a new, fast approach to inferring random walk properties based on graph neural networks (GNNs).
Statistical Tests for Force Inference in Heterogeneous Environments
We devise a method to detect and estimate forces in a heterogeneous environment based on experimentally recorded stochastic trajectories.
Biological Physics Chemical Physics Biomolecules Quantitative Methods
