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2020 – today
- 2025
[j3]Kevin Batz
, Joost-Pieter Katoen, Francesca Randone, Tobias Winkler:
Foundations for Deductive Verification of Continuous Probabilistic Programs: From Lebesgue to Riemann and Back. Proc. ACM Program. Lang. 9(OOPSLA1): 421-448 (2025)- [i5]Kevin Batz, Joost-Pieter Katoen, Francesca Randone, Tobias Winkler:
Foundations for Deductive Verification of Continuous Probabilistic Programs: From Lebesgue to Riemann and Back. CoRR abs/2502.19388 (2025) - 2024
- [j2]Francesca Randone, Luca Bortolussi, Emilio Incerto, Mirco Tribastone:
Inference of Probabilistic Programs with Moment-Matching Gaussian Mixtures. Proc. ACM Program. Lang. 8(POPL): 1882-1912 (2024) - [c6]Philipp Schröer, Francesca Randone, Raúl Pardo, Andrzej Wasowski:
Symbolic Quantitative Information Flow for Probabilistic Programs. Principles of Verification (1) 2024: 128-154 - [c5]Francesca Randone, Romina Doz, Francesca Cairoli, Luca Bortolussi:
Towards a Probabilistic Programming Approach to Analyse Collective Adaptive Systems. ISoLA (1) 2024: 168-185 - [i4]Philipp Schröer, Francesca Randone, Raúl Pardo, Andrzej Wasowski:
Symbolic Quantitative Information Flow for Probabilistic Programs. CoRR abs/2412.00907 (2024) - 2023
- [i3]Francesca Randone, Luca Bortolussi, Emilio Incerto, Mirco Tribastone:
Inference of Probabilistic Programs with Moment-Matching Gaussian Mixtures. CoRR abs/2311.08235 (2023) - 2022
- [c4]Francesca Randone, Luca Bortolussi, Mirco Tribastone:
Jump Longer to Jump Less: Improving Dynamic Boundary Projection with h-Scaling. QEST 2022: 150-170 - 2021
- [j1]Francesca Randone, Luca Bortolussi, Mirco Tribastone:
Refining Mean-field Approximations by Dynamic State Truncation. Proc. ACM Meas. Anal. Comput. Syst. 5(2): 25:1-25:30 (2021) - [c3]Marco Virgolin, Andrea De Lorenzo, Francesca Randone, Eric Medvet, Mattias Wahde:
Model learning with personalized interpretability estimation (ML-PIE). GECCO Companion 2021: 1355-1364 - [c2]Francesca Randone, Luca Bortolussi, Mirco Tribastone:
Refining Mean-field Approximations by Dynamic State Truncation. SIGMETRICS (Abstracts) 2021: 31-32 - [i2]Marco Virgolin, Andrea De Lorenzo, Francesca Randone, Eric Medvet, Mattias Wahde:
Model Learning with Personalized Interpretability Estimation (ML-PIE). CoRR abs/2104.06060 (2021) - 2020
- [c1]Marco Virgolin, Andrea De Lorenzo, Eric Medvet, Francesca Randone:
Learning a Formula of Interpretability to Learn Interpretable Formulas. PPSN (2) 2020: 79-93 - [i1]Marco Virgolin, Andrea De Lorenzo, Eric Medvet, Francesca Randone:
Learning a Formula of Interpretability to Learn Interpretable Formulas. CoRR abs/2004.11170 (2020)
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