Deep Statistical Model Checking
DOI10.1007/978-3-030-50086-3_6OpenAlexW3035170447MaRDI QIDQ5041276
Timo P. Gros, Holger Hermanns, Marcel Steinmetz, Jörg Hoffmann, Michaela Klauck
Publication date: 13 October 2022
Published in: Formal Techniques for Distributed Objects, Components, and Systems (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-030-50086-3_6
Artificial neural networks and deep learning (68T07) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Markov and semi-Markov decision processes (90C40) Specification and verification (program logics, model checking, etc.) (68Q60) Probability in computer science (algorithm analysis, random structures, phase transitions, etc.) (68Q87)
Uses Software
Cites Work
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- Some inequalities relating to the partial sum of binomial probabilities
- A logic for reasoning about time and reliability
- Multilayer feedforward networks are universal approximators
- Safety verification of deep neural networks
- Reluplex: an efficient SMT solver for verifying deep neural networks
- Stochastic Model Checking
- Explicit Model Checking of Very Large MDP Using Partitioning and Secondary Storage
- Exact and ordinary lumpability in finite Markov chains
- Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks
- A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
- Sequential Tests of Statistical Hypotheses
- Verification, Model Checking, and Abstract Interpretation
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