3 papers
cs.LG2026
Explaining a probabilistic prediction on the simplex with Shapley compositions
Paul-Gauthier Noé, Miquel Perelló-Nieto, Jean-François Bonastre +1
Originating in game theory, Shapley values are widely used for explaining a machine learning model's prediction by quantifying the contribution of each feature's value to the predi…
cs.AI2026
Continual learning and refinement of causal models through dynamic predicate invention
Enrique Crespo-Fernandez, Oliver Ray, Telmo de Menezes e Silva Filho +1
Efficiently navigating complex environments requires agents to internalize the underlying logic of their world, yet standard world modelling methods often struggle with sample inef…
cs.LG2025
Evaluating classification performance across operating contexts: A comparison of decision curve analysis and cost curves
Louise AC Millard, Peter A Flach
Classification models typically predict a score and use a decision threshold to produce a classification. Appropriate model evaluation should carefully consider the context in whic…