11 citations · 25 across the 10 of their papers we have counts for
15 papers
Deductive Controller Synthesis for Probabilistic Hyperproperties
Roman Andriushchenko, Ezio Bartocci, Milan Ceska +2
Probabilistic hyperproperties specify quantitative relations between the probabilities of reaching different target sets of states from different initial sets of states. This class…
Designing Approximate Arithmetic Circuits with Combined Error Constraints
Milan Češka, Jiří Matyáš, Vojtech Mrazek +1
Approximate circuits trading the power consumption for the quality of results play a key role in the development of energy-aware systems. Designing complex approximate circuits is,…
Abstraction-Based Segmental Simulation of Chemical Reaction Networks
Martin Helfrich, Milan Češka, Jan Křetínský +1
Simulating chemical reaction networks is often computationally demanding, in particular due to stiffness. We propose a novel simulation scheme where long runs are not simulated as…
Inductive Synthesis of Finite-State Controllers for POMDPs
Roman Andriushchenko, Milan Ceska, Sebastian Junges +1
We present a novel learning framework to obtain finite-state controllers (FSCs) for partially observable Markov decision processes and illustrate its applicability for indefinite-h…
Model Repair Revamped: On the Automated Synthesis of Markov Chains
Milan Ceska, Christian Dehnert, Nils Jansen +2
This paper outlines two approaches|based on counterexample-guided abstraction refinement (CEGAR) and counterexample-guided inductive synthesis (CEGIS), respectively to the automate…
Inductive Synthesis for Probabilistic Programs Reaches New Horizons
Roman Andriushchenko, Milan Ceska, Sebastian Junges +1
This paper presents a novel method for the automated synthesis of probabilistic programs. The starting point is a program sketch representing a finite family of finite-state Markov…