| Feature-Guided Black-Box Safety Testing of Deep Neural Networks M Wicker, X Huang, M Kwiatkowska Tools and Algorithms for the Construction and Analysis of Systems (TACAS …, 2017 | 271 | 2017 |
| A game-based approximate verification of deep neural networks with provable guarantees M Wu, M Wicker, W Ruan, X Huang, M Kwiatkowska Theoretical Computer Science 807, 298-329, 2020 | 132 | 2020 |
| Uncertainty quantification with statistical guarantees in end-to-end autonomous driving control R Michelmore, M Wicker, L Laurenti, L Cardelli, Y Gal, M Kwiatkowska 2020 IEEE International Conference on Robotics and Automation (ICRA), 7344-7350, 2020 | 109 | 2020 |
| Robustness of 3D Deep Learning in an Adversarial Setting M Wicker, M Kwiatkowska Computer Vision and Pattern Recognition (CVPR 2019), 2019 | 91 | 2019 |
| Robustness of Bayesian Neural Networks to Gradient-Based Attacks G Carbone, M Wicker, L Laurenti, A Patane, L Bortolussi, G Sanguinetti Neural Information Processing Systems (NeurIPS 2020), 2020 | 84 | 2020 |
| Statistical Guarantees for the Robustness of Bayesian Neural Networks L Cardelli, M Kwiatkowska, L Laurenti, N Paoletti, A Patane, M Wicker International Joint Conference on Artificial Intelligence (IJCAI 2019), 2019 | 69 | 2019 |
| Probabilistic Safety for Bayesian Neural Networks M Wicker, L Laurenti, A Patane, M Kwiatkowska Conference on Uncertainty in Artificial Intelligence (UAI 2020), 2020 | 56 | 2020 |
| Bayesian Inference with Certifiable Adversarial Robustness M Wicker, L Laurenti, A Patane, Z Chen, Z Zhang, M Kwiatkowska 24th International Conference on Artificial Intelligence and Statistics …, 2021 | 39 | 2021 |
| Optimal learning of Markov k-tree topology D Chang, L Ding, R Malmberg, D Robinson, M Wicker, H Yan, A Martinez, ... Journal of Computational Mathematics and Data Science 4, 100046, 2022 | 33 | 2022 |
| Efficient Learning of Optimal Markov Network Topology with k-Tree Modeling L Ding, D Chang, R Malmberg, A Martinez, D Robinson, M Wicker, H Yan, ... arXiv preprint arXiv:1801.06900, 2018 | 24 | 2018 |
| Individual Fairness Guarantees for Neural Networks E Benussi, A Patane, M Wicker, L Laurenti, M Kwiatkowska arXiv preprint arXiv:2205.05763, 2022 | 20 | 2022 |
| Certification of iterative predictions in Bayesian neural networks M Wicker, L Laurenti, A Patane, N Paoletti, A Abate, M Kwiatkowska Uncertainty in Artificial Intelligence, 1713-1723, 2021 | 15 | 2021 |
| Gradient-Free Adversarial Attacks for Bayesian Neural Networks M Yuan, M Wicker, L Laurenti Advances in Approximate Bayesian Inference (AABI 2021), arXiv:2012.12640, 2020 | 15 | 2020 |
| Robust Explanation Constraints for Neural Networks M Wicker, J Heo, L Costabello, A Weller arXiv, 2022 | 13 | 2022 |
| Tractable Uncertainty for Structure Learning B Wang, MR Wicker, M Kwiatkowska International Conference on Machine Learning, 23131-23150, 2022 | 8 | 2022 |
| On the robustness of bayesian neural networks to adversarial attacks L Bortolussi, G Carbone, L Laurenti, A Patane, G Sanguinetti, M Wicker IEEE Transactions on Neural Networks and Learning Systems, 2024 | 6 | 2024 |
| Adversarial Robustness Certification for Bayesian Neural Networks M Wicker, A Patane, L Laurenti, M Kwiatkowska arXiv, https://arxiv.org/pdf/2306.13614.pdf, 2023 | 2 | 2023 |
| Individual Fairness in Bayesian Neural Networks A Doherty, M Wicker, L Laurenti, A Patane arXiv preprint arXiv:2304.10828, 2023 | 2 | 2023 |
| Emergent Linguistic Structures in Neural Networks are Fragile E La Malfa, M Wicker, M Kwiatkowska arXiv preprint arXiv:2210.17406, 2022 | 2 | 2022 |
| Adversarial robustness of Bayesian neural networks M Wicker University of Oxford, 2021 | 2 | 2021 |
Marta KwiatkowskaProfessor of Computing Systems, University of Oxford在 comlab.ox.ac.uk 的电子邮件经过验证
