Feature-Guided Black-Box Safety Testing of Deep Neural Networks. - Matthew Wicker; Xiaowei Huang 001; Marta Kwiatkowska (TACAS (1), 2018)

Efficient Learning of Optimal Markov Network Topology with k-Tree Modeling. - Liang Ding 007; Di Chang; Russell L. Malmberg; Aaron Martínez; David Robinson; Matthew Wicker; Hongfei Yan; Liming Cai (CoRR, 2018)

Robustness of 3D Deep Learning in an Adversarial Setting. - Matthew Wicker; Marta Kwiatkowska (CVPR, 2019)

Statistical Guarantees for the Robustness of Bayesian Neural Networks. - Luca Cardelli; Marta Kwiatkowska; Luca Laurenti; Nicola Paoletti; Andrea Patane; Matthew Wicker (IJCAI, 2019)

Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control. - Rhiannon Michelmore; Matthew Wicker; Luca Laurenti; Luca Cardelli; Yarin Gal; Marta Kwiatkowska (ICRA, 2020)

Robustness of Bayesian Neural Networks to Gradient-Based Attacks. - Ginevra Carbone; Matthew Wicker; Luca Laurenti; Andrea Patané; Luca Bortolussi; Guido Sanguinetti (NeurIPS, 2020)

Probabilistic Safety for Bayesian Neural Networks. - Matthew Wicker; Luca Laurenti; Andrea Patane; Marta Kwiatkowska (UAI, 2020)

Gradient-Free Adversarial Attacks for Bayesian Neural Networks. - Matthew Yuan; Matthew Wicker; Luca Laurenti (CoRR, 2020)

A game-based approximate verification of deep neural networks with provable guarantees. - Min Wu 011; Matthew Wicker; Wenjie Ruan; Xiaowei Huang 001; Marta Kwiatkowska (Theor. Comput. Sci., 2020)

Bayesian Inference with Certifiable Adversarial Robustness. - Matthew Wicker; Luca Laurenti; Andrea Patane; Zhuotong Chen; Zheng Zhang; Marta Kwiatkowska (AISTATS, 2021)

Certification of iterative predictions in Bayesian neural networks. - Matthew Wicker; Luca Laurenti; Andrea Patane; Nicola Paoletti; Alessandro Abate; Marta Kwiatkowska (UAI, 2021)

Tractable Uncertainty for Structure Learning. - Benjie Wang 001; Matthew Wicker; Marta Kwiatkowska (ICML, 2022)

Individual Fairness Guarantees for Neural Networks. - Elias Benussi; Andrea Patanè; Matthew Wicker; Luca Laurenti; Marta Kwiatkowska (IJCAI, 2022)

Emergent Linguistic Structures in Neural Networks are Fragile. - Emanuele La Malfa; Matthew Wicker; Marta Kiatkowska (CoRR, 2022)

Robust Explanation Constraints for Neural Networks. - Matthew Wicker; Juyeon Heo; Luca Costabello; Adrian Weller (ICLR, 2023)

Use perturbations when learning from explanations. - Juyeon Heo; Vihari Piratla; Matthew Wicker; Adrian Weller (NeurIPS, 2023)

Certification of Distributional Individual Fairness. - Matthew Wicker; Vihari Piratla; Adrian Weller (NeurIPS, 2023)

Robust Learning from Explanations. - Juyeon Heo; Vihari Piratla; Matthew Wicker; Adrian Weller (CoRR, 2023)

Individual Fairness in Bayesian Neural Networks. - Alice Doherty; Matthew Wicker; Luca Laurenti; Andrea Patane (CoRR, 2023)

Adversarial Robustness Certification for Bayesian Neural Networks. - Matthew Wicker; Andrea Patane; Luca Laurenti; Marta Kwiatkowska (FM (1), 2024)

Probabilistic reach-avoid for Bayesian neural networks. - Matthew Wicker; Luca Laurenti; Andrea Patane; Nicola Paoletti; Alessandro Abate; Marta Kwiatkowska (Artif. Intell., 2024)

Certified Robustness to Data Poisoning in Gradient-Based Training. - Philip Sosnin; Mark Niklas Müller; Maximilian Baader; Calvin Tsay; Matthew Wicker (CoRR, 2024)

Certificates of Differential Privacy and Unlearning for Gradient-Based Training. - Matthew Wicker; Philip Sosnin; Adrianna Janik; Mark N. Müller; Adrian Weller; Calvin Tsay (CoRR, 2024)

Certifiably Quantisation-Robust training and inference of Neural Networks. - Hue Dang; Matthew Wicker; Goetz Botterweck; Andrea Patane (AISTATS, 2025)

On the Robustness of Bayesian Neural Networks to Adversarial Attacks. - Luca Bortolussi; Ginevra Carbone; Luca Laurenti; Andrea Patane; Guido Sanguinetti; Matthew Wicker (IEEE Trans. Neural Networks Learn. Syst., 2025)

Model Guidance via Robust Feature Attribution. - Mihnea Ghitu; Matthew Wicker; Vihari Piratla (CoRR, 2025)