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cs.LG2024
SMLP: Symbolic Machine Learning Prover (User Manual)
Franz Brauße, Zurab Khasidashvili, Konstantin Korovin
SMLP: Symbolic Machine Learning Prover an open source tool for exploration and optimization of systems represented by machine learning models. SMLP uses symbolic reasoning for ML m…
cs.LG2024
SMLP: Symbolic Machine Learning Prover
Franz Brauße, Zurab Khasidashvili, Konstantin Korovin
Symbolic Machine Learning Prover (SMLP) is a tool and a library for system exploration based on data samples obtained by simulating or executing the system on a number of input vec…
cs.LG2021
Bayesian Optimisation with Formal Guarantees
Franz Brauße, Zurab Khasidashvili, Konstantin Korovin
Application domains of Bayesian optimization include optimizing black-box functions or very complex functions. The functions we are interested in describe complex real-world system…