The role of invariance in spectral complexity-based generalization bounds K Pitas, A Loukas, M Davies, P Vandergheynst NeurIPS 2019 Workshop on Machine Learning with Guarantees, Vancouver, Canada., 2019 | 15* | 2019 |
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation K Pitas Proceedings of the 37th International Conference on Machine Learning, PMLR …, 2020 | 13* | 2020 |
Cold Posteriors through PAC-Bayes K Pitas, J Arbel NeurIPS 2022 Workshop on Trustworthy and Socially Responsible Machine …, 2022 | 6 | 2022 |
A Primer on Bayesian Neural Networks: Review and Debates J Arbel, K Pitas, M Vladimirova, V Fortuin stat 1050, 28, 2023 | 3 | 2023 |
Something for (almost) nothing: Improving deep ensemble calibration using unlabeled data K Pitas, J Arbel arXiv preprint arXiv:2310.02885, 2023 | | 2023 |
The fine print on tempered posteriors K Pitas, J Arbel The 15th Asian Conference in Machine Learning, ACML, PMLR 2023, 2023 | | 2023 |
On Vacuous and Non-Vacuous Generalization Bounds for Deep Neural Networks. K Pitas EPFL, 2020 | | 2020 |
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation–Appendix K Pitas Proceedings of the 37th International Conference on Machine Learning, PMLR …, 2020 | | 2020 |
Disjunctive Programming for Parametric Dictionary Learning on Multi-Layer Graphs P Konstantinos Ecole Polytechnique Federale de Lausanne, 2015 | | 2015 |