🏢 KU Leuven

CMR: A novel Concept-Based Memory Reasoner delivers human-understandable, verifiable AI task predictions by using a neural selection mechanism over a set of human-understandable logic rules, achievin…

Speed up repeated evasion attacks on tree ensembles by 36x using feature perturbation insights!

Credal Deep Ensembles (CreDEs) improve uncertainty quantification in deep learning by predicting probability intervals, enhancing accuracy and calibration, particularly for out-of-distribution data.

Revolutionizing probabilistic inference, PLIA₁ uses tensor operations and FFT to scale integer arithmetic, achieving orders-of-magnitude speedup in inference and learning times.