3 papers
cs.LO2026
Don't Blame the Model, Verify the Data: An Evaluation of SMT-based Dataset Verification (Extended Version)
Sehee Park, Dominik Geißler, Andrei Aleksandrov +1
The EU AI Act mandates that datasets for high-risk machine learning (ML) systems meet strict quality criteria such as soundness and bias mitigation. While Satisfiability Modulo The…
cs.FL2025
Probabilistic Programming Meets Automata Theory: Exact Inference using Weighted Automata
Dominik Geißler, Tobias Winkler
Probabilistic programs encode stochastic models as ordinary-looking programs with primitives for sampling numbers from predefined distributions and conditioning. Their applications…
cs.FL2025
Weighted Automata for Exact Inference in Discrete Probabilistic Programs
Dominik Geißler, Tobias Winkler
In probabilistic programming, the inference problem asks to determine a program's posterior distribution conditioned on its "observe" instructions. Inference is challenging, especi…