| Pointless learning F Clerc, V Danos, F Dahlqvist, I Garnier Foundations of Software Science and Computation Structures: 20th …, 2017 | 43 | 2017 |
| Expressiveness of probabilistic modal logics: A gradual approach F Clerc, N Fijalkow, B Klin, P Panangaden Information and Computation 267, 145-163, 2019 | 11 | 2019 |
| Presenting a category modulo a rewriting system F Clerc, S Mimram 26th International Conference on Rewriting Techniques and Applications (RTA …, 2015 | 11 | 2015 |
| Bicategories of Markov processes F Clerc, H Humphrey, P Panangaden Models, Algorithms, Logics and Tools: Essays Dedicated to Kim Guldstrand …, 2017 | 10 | 2017 |
| PAC-Bayesian generalization bounds for adversarial generative models SD Mbacke, F Clerc, P Germain International Conference on Machine Learning, 24271-24290, 2023 | 8 | 2023 |
| Statistical guarantees for variational autoencoders using pac-bayesian theory SD Mbacke, F Clerc, P Germain Advances in Neural Information Processing Systems 36, 2024 | 5 | 2024 |
| Bisimulation for feller-dynkin processes L Chen, F Clerc, P Panangaden Electronic Notes in Theoretical Computer Science 347, 45-63, 2019 | 5 | 2019 |
| Towards a classification of behavioural equivalences in continuous-time Markov processes L Chen, F Clerc, P Panangaden Electronic Notes in Theoretical Computer Science 352, 53-77, 2020 | 3 | 2020 |
| Behavioural equivalences for continuous-time Markov processes L Chen, F Clerc, P Panangaden Mathematical Structures in Computer Science 33 (4-5), 222-258, 2023 | 1 | 2023 |
| Bisimulation and behavioural equivalences for continuous-time Markov processes F Clerc McGill University (Canada), 2021 | 1 | 2021 |
| Behavioural pseudometrics for continuous-time diffusions L Chen, F Clerc, P Panangaden arXiv preprint arXiv:2312.16729, 2023 | | 2023 |
| Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory S Diarra Mbacke, F Clerc, P Germain arXiv e-prints, arXiv: 2310.04935, 2023 | | 2023 |
| Sample Boosting Algorithm (SamBA)-An interpretable greedy ensemble classifier based on local expertise for fat data B Bauvin, C Capponi, F Clerc, P Germain, S Koço, J Corbeil Uncertainty in Artificial Intelligence, 130-140, 2023 | | 2023 |
| PAC-Bayesian Generalization Bounds for Adversarial Generative Models S Diarra Mbacke, F Clerc, P Germain arXiv e-prints, arXiv: 2302.08942, 2023 | | 2023 |
| Semantics for probabilistic programming F Clerc, V Danos, F Dahlqvist, I Garnier | | 2016 |
| COMP 599: Constructing a metric between labelled Markov processes F Clerc | | 2016 |
| Sample Boosting Algorithm (SamBA)-An Interpretable Greedy Ensemble Classifier Based On Local Expertise For Fat Data (Supplementary Material) B Bauvin, C Capponi, F Clerc, P Germain, S Koço, J Corbeil | | |
| Pointless learning (draft) F Clerc, V Danos, F Dahlqvist, I Garnier | | |
| Towards a categorical understanding of variety theorems for quantitative algebras W Boshuck, F Clerc, P Panangaden CALCO EARLY IDEAS 2017, 2, 0 | | |
