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Matthew Wicker
Matthew Wicker
Imperial College London & The Alan Turing Institute
Verified email at imperial.ac.uk - Homepage
Title
Cited by
Cited by
Year
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
2902017
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
1382020
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
1372020
Robustness of 3D Deep Learning in an Adversarial Setting
M Wicker, M Kwiatkowska
Computer Vision and Pattern Recognition (CVPR 2019), 2019
1162019
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
942020
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
722019
Probabilistic Safety for Bayesian Neural Networks
M Wicker, L Laurenti, A Patane, M Kwiatkowska
Conference on Uncertainty in Artificial Intelligence (UAI 2020), 2020
642020
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
422021
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
382022
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
252018
Individual Fairness Guarantees for Neural Networks
E Benussi, A Patane, M Wicker, L Laurenti, M Kwiatkowska
arXiv preprint arXiv:2205.05763, 2022
242022
Robust Explanation Constraints for Neural Networks
M Wicker, J Heo, L Costabello, A Weller
arXiv, 2022
212022
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
172024
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
172020
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
162021
Tractable Uncertainty for Structure Learning
B Wang, MR Wicker, M Kwiatkowska
International Conference on Machine Learning, 23131-23150, 2022
122022
Certified Robustness to Data Poisoning in Gradient-Based Training
P Sosnin, MN Müller, M Baader, C Tsay, M Wicker
arXiv preprint arXiv:2406.05670, 2024
92024
Probabilistic reach-avoid for Bayesian neural networks
M Wicker, L Laurenti, A Patane, N Paoletti, A Abate, M Kwiatkowska
Artificial Intelligence 334, 104132, 2024
42024
Individual Fairness in Bayesian Neural Networks
A Doherty, M Wicker, L Laurenti, A Patane
arXiv preprint arXiv:2304.10828, 2023
42023
Adversarial Robustness Certification for Bayesian Neural Networks
M Wicker, A Patane, L Laurenti, M Kwiatkowska
arXiv, https://arxiv.org/pdf/2306.13614.pdf, 2023
32023
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Articles 1–20