DeepAbstract: neural network abstraction for accelerating verification P Ashok, V Hashemi, J Křetínský, S Mohr International Symposium on Automated Technology for Verification and …, 2020 | 56 | 2020 |
Gaussian-based runtime detection of out-of-distribution inputs for neural networks V Hashemi, J Křetínský, S Mohr, E Seferis International Conference on Runtime Verification, 254-264, 2021 | 6 | 2021 |
Assessment of neural networks for stream-water-temperature prediction S Mohr, K Drainas, J Geist 2021 20th IEEE International Conference on Machine Learning and Applications …, 2021 | 5 | 2021 |
Predicting stream water temperature with artificial neural networks based on open‐access data K Drainas, L Kaule, S Mohr, B Uniyal, R Wild, J Geist Hydrological Processes 37 (10), e14991, 2023 | 3 | 2023 |
Stochastic games with lexicographic objectives K Chatterjee, JP Katoen, S Mohr, M Weininger, T Winkler Formal Methods in System Design, 1-41, 2023 | 3 | 2023 |
Learning Explainable and Better Performing Representations of POMDP Strategies A Bork, D Chakraborty, K Grover, J Křetínský, S Mohr International Conference on Tools and Algorithms for the Construction and …, 2024 | 1 | 2024 |
Syntactic vs Semantic Linear Abstraction and Refinement of Neural Networks C Chau, J Křetínský, S Mohr International Symposium on Automated Technology for Verification and …, 2023 | | 2023 |
REACTIONS IN ORGANIC-CRYSTALS. 3. TRISPIRO-PYRROLOISOQUINOLINES VIA ASYMMETRIC PHOTO-DIMERIZATION AND H-ABSTRACTION IN CRYSTALLINE CYCLOHEXYLIDENE-PHENYL-5 (4H) OXAZOLONES S MOHR TETRAHEDRON LETTERS, 3139-3140, 1979 | | 1979 |
EDCC 2020 P Ashok, AA Nair, S Mohr, S Mohseni, H Khosrowjerdi, P Folkesson, ... | | |