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Found 6 papers, 1 papers with code
Causal discovery for time series with constraint-based model and PMIME measure
To circumvent this problem, we present in this paper a novel approach for discovering causality in time series data that combines a causal discovery algorithm with an information theoretic-based measure.
A New Approach for Explainable Multiple Organ Annotation with Few Data
In this paper, we focus on organ annotation in medical images and we introduce a reasoning framework that is based on learning fuzzy relations on a small dataset for generating explanations.
Embedded Constrained Feature Construction for High-Energy Physics Data Classification
Before any publication, data analysis of high-energy physics experiments must be validated.
Sim-to-Real Domain Adaptation For High Energy Physics
Particle physics or High Energy Physics (HEP) studies the elementary constituents of matter and their interactions with each other.
Consistent Feature Construction with Constrained Genetic Programming for Experimental Physics
To the best of our knowledge, it is the first time a method is proposed for interpretable feature construction with units of measurement, and that experts in high-energy physics validate the overall approach as well as the interpretability of the built features.
