1 citations · 1 across the 3 of their papers we have counts for
3 papers
The Theory and Practice of MAP Inference over Non-Convex Constraints
Leander Kurscheidt, Gabriele Masina, Roberto Sebastiani +1
In many safety-critical settings, probabilistic ML systems have to make predictions subject to algebraic constraints, e.g., predicting the most likely trajectory that does not cros…
A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction
Leander Kurscheidt, Paolo Morettin, Roberto Sebastiani +2
In safety-critical applications, guaranteeing the satisfaction of constraints over continuous environments is crucial, e.g., an autonomous agent should never crash into obstacles o…
Probabilistic ML Verification via Weighted Model Integration
Paolo Morettin, Andrea Passerini, Roberto Sebastiani
In machine learning (ML) verification, the majority of procedures are non-quantitative and therefore cannot be used for verifying probabilistic models, or be applied in domains whe…