| Closed-form continuous-time neural networks R Hasani, M Lechner, A Amini, L Liebenwein, A Ray, M Tschaikowski, ... Nature Machine Intelligence 4 (11), 992-1003, 2022 | 76 | 2022 |
| Forward and backward bisimulations for chemical reaction networks L Cardelli, M Tribastone, M Tschaikowski, A Vandin 26th International Conference on Concurrency Theory, CONCUR 2015 42, 226-239, 2015 | 67 | 2015 |
| ERODE: a tool for the evaluation and reduction of ordinary differential equations L Cardelli, M Tribastone, M Tschaikowski, A Vandin Tools and Algorithms for the Construction and Analysis of Systems: 23rd …, 2017 | 66 | 2017 |
| Maximal aggregation of polynomial dynamical systems L Cardelli, M Tribastone, M Tschaikowski, A Vandin Proceedings of the National Academy of Sciences 114 (38), 10029-10034, 2017 | 63 | 2017 |
| Symbolic computation of differential equivalences L Cardelli, M Tribastone, M Tschaikowski, A Vandin ACM SIGPLAN Notices 51 (1), 137-150, 2016 | 60 | 2016 |
| Exact fluid lumpability for Markovian process algebra M Tschaikowski, M Tribastone CONCUR 2012–Concurrency Theory: 23rd International Conference, CONCUR 2012 …, 2012 | 54 | 2012 |
| PID control of biochemical reaction networks M Whitby, L Cardelli, M Kwiatkowska, L Laurenti, M Tribastone, ... IEEE Transactions on Automatic Control 67 (2), 1023-1030, 2021 | 51 | 2021 |
| Efficient syntax-driven lumping of differential equations L Cardelli, M Tribastone, M Tschaikowski, A Vandin International Conference on Tools and Algorithms for the Construction and …, 2016 | 42 | 2016 |
| Noise reduction in complex biological switches L Cardelli, A Csikász-Nagy, N Dalchau, M Tribastone, M Tschaikowski Scientific reports 6 (1), 20214, 2016 | 40 | 2016 |
| Approximate reduction of heterogenous nonlinear models with differential hulls M Tschaikowski, M Tribastone IEEE Transactions on Automatic Control 61 (4), 1099-1104, 2015 | 40 | 2015 |
| Comparing chemical reaction networks: A categorical and algorithmic perspective L Cardelli, M Tribastone, M Tschaikowski, A Vandin Proceedings of the 31st Annual ACM/IEEE Symposium on Logic in Computer …, 2016 | 36 | 2016 |
| Scaling size and parameter spaces in variability-aware software performance models (t) M Kowal, M Tschaikowski, M Tribastone, I Schaefer 2015 30th IEEE/ACM International Conference on Automated Software …, 2015 | 35 | 2015 |
| From electric circuits to chemical networks L Cardelli, M Tribastone, M Tschaikowski Natural Computing 19, 237-248, 2020 | 34 | 2020 |
| Tackling continuous state-space explosion in a Markovian process algebra M Tschaikowski, M Tribastone Theoretical Computer Science 517, 1-33, 2014 | 30 | 2014 |
| Syntactic Markovian bisimulation for chemical reaction networks L Cardelli, M Tribastone, M Tschaikowski, A Vandin Models, Algorithms, Logics and Tools: Essays Dedicated to Kim Guldstrand …, 2017 | 29 | 2017 |
| Spatial fluid limits for stochastic mobile networks M Tschaikowski, M Tribastone Performance Evaluation 109, 52-76, 2017 | 28* | 2017 |
| A unified framework for differential aggregations in Markovian process algebra M Tschaikowski, M Tribastone Journal of Logical and Algebraic Methods in Programming 84 (2), 238-258, 2015 | 26 | 2015 |
| Closed-form continuous-depth models R Hasani, M Lechner, A Amini, L Liebenwein, M Tschaikowski, G Teschl, ... arXiv preprint arXiv:2106.13898, 2021 | 25 | 2021 |
| Symbolic computation of differential equivalences L Cardelli, M Tribastone, M Tschaikowski, A Vandin Theoretical Computer Science 777, 132-154, 2019 | 25 | 2019 |
| Guaranteed error bounds on approximate model abstractions through reachability analysis L Cardelli, M Tribastone, M Tschaikowski, A Vandin Quantitative Evaluation of Systems: 15th International Conference, QEST 2018 …, 2018 | 24 | 2018 |
Mirco TribastoneIMT LuccaVerified email at imtlucca.it
