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20242026
most citedRecovery and inference of causal effects with sequential adjustment for confounding and attrition

3 citations · 3 across the 5 of their papers we have counts for

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cs.LG2026

path_boost: A Python Package for Interpretable Graph-Level Prediction using Path-Based Gradient Boosting

Claudio Meggio, Johan Pensar, Riccardo De Bin

We present path_boost, a Python package for interpretable supervised learning on graph-structured input data. The package implements PathBoost, a gradient boosting algorithm that a…

physics.chem-ph2026

tmQM-RDF Dataset: a Knowledge Graph Representing Transition Metal Complexes

Luca Cibinel, Trond Linjordet, Johan Pensar +3

Transition Metal Complexes (TMCs) have wide-ranging practical utility in chemistry, with possible applications that range from catalysis to medicinal chemistry. The study of TMCs a…