| A Primer on Bayesian Neural Networks: Review and Debates J Arbel, K Pitas, M Vladimirova, V Fortuin stat 1050, 28, 2023 | 20 | 2023 |
| 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 | 18* | 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 |
| The fine print on tempered posteriors K Pitas, J Arbel The 15th Asian Conference in Machine Learning, ACML, PMLR 2023, 2023 | 4 | 2023 |
| Just rephrase it! Uncertainty estimation in closed-source language models via multiple rephrased queries A Yang, C Chen, K Pitas arXiv preprint arXiv:2405.13907, 2024 | 3 | 2024 |
| Just rotate it! Uncertainty estimation in closed-source models via multiple queries K Pitas, J Arbel arXiv preprint arXiv:2405.13864, 2024 | | 2024 |
| Improving Deep Ensembles without Communication K Pitas, M Arbel, J Arbel Workshop on Advancing Neural Network Training: Computational Efficiency …, 2023 | | 2023 |
| Something for (almost) nothing: Improving deep ensemble calibration using unlabeled data K Pitas, J Arbel arXiv preprint arXiv:2310.02885, 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 |
