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cs.LG2025
Interpretable Causal Representation Learning for Biological Data in the Pathway Space
Jesus de la Fuente, Robert Lehmann, Carlos Ruiz-Arenas +8
Predicting the impact of genomic and drug perturbations in cellular function is crucial for understanding gene functions and drug effects, ultimately leading to improved therapies.…
cs.LG2025★ 7 cited
REX: Causal discovery based on machine learning and explainability techniques
Jesus Renero, Idoia Ochoa, Roberto Maestre
Explainable Artificial Intelligence (XAI) techniques hold significant potential for enhancing the causal discovery process, which is crucial for understanding complex systems in ar…