Matthew Wicker

According to our database, Matthew Wicker authored at least 24 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

Certified Robustness to Data Poisoning in Gradient-Based Training.

Philip Sosnin, Mark Niklas Müller, Maximilian Baader, Calvin Tsay, Matthew Wicker

CoRR, 2024

Probabilistic reach-avoid for Bayesian neural networks.

Matthew Wicker, Luca Laurenti, Andrea Patane, Nicola Paoletti, Alessandro Abate, Marta Kwiatkowska

Artif. Intell., 2024

Adversarial Robustness Certification for Bayesian Neural Networks.

Matthew Wicker, Andrea Patane, Luca Laurenti, Marta Kwiatkowska

Proceedings of the Formal Methods - 26th International Symposium, 2024

2023

Individual Fairness in Bayesian Neural Networks.

Alice Doherty, Matthew Wicker, Luca Laurenti, Andrea Patane

CoRR, 2023

Robust Learning from Explanations.

Juyeon Heo, Vihari Piratla, Matthew Wicker, Adrian Weller

CoRR, 2023

Certification of Distributional Individual Fairness.

Matthew Wicker, Vihari Piratla, Adrian Weller

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Use perturbations when learning from explanations.

Juyeon Heo, Vihari Piratla, Matthew Wicker, Adrian Weller

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Robust Explanation Constraints for Neural Networks.

Matthew Wicker, Juyeon Heo, Luca Costabello, Adrian Weller

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Emergent Linguistic Structures in Neural Networks are Fragile.

Emanuele La Malfa, Matthew Wicker, Marta Kiatkowska

CoRR, 2022

On the Robustness of Bayesian Neural Networks to Adversarial Attacks.

Luca Bortolussi, Ginevra Carbone, Luca Laurenti, Andrea Patane, Guido Sanguinetti, Matthew Wicker

CoRR, 2022

Individual Fairness Guarantees for Neural Networks.

Elias Benussi, Andrea Patanè, Matthew Wicker, Luca Laurenti, Marta Kwiatkowska

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Tractable Uncertainty for Structure Learning.

Benjie Wang, Matthew Wicker, Marta Kwiatkowska

Proceedings of the International Conference on Machine Learning, 2022

2021

Certification of iterative predictions in Bayesian neural networks.

Matthew Wicker, Luca Laurenti, Andrea Patane, Nicola Paoletti, Alessandro Abate, Marta Kwiatkowska

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Bayesian Inference with Certifiable Adversarial Robustness.

Matthew Wicker, Luca Laurenti, Andrea Patane, Zhuotong Chen, Zheng Zhang, Marta Kwiatkowska

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

A game-based approximate verification of deep neural networks with provable guarantees.

Min Wu, Matthew Wicker, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska

Theor. Comput. Sci., 2020

Gradient-Free Adversarial Attacks for Bayesian Neural Networks.

Matthew Yuan, Matthew Wicker, Luca Laurenti

CoRR, 2020

Probabilistic Safety for Bayesian Neural Networks.

Matthew Wicker, Luca Laurenti, Andrea Patane, Marta Kwiatkowska

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Robustness of Bayesian Neural Networks to Gradient-Based Attacks.

Ginevra Carbone, Matthew Wicker, Luca Laurenti, Andrea Patané, Luca Bortolussi, Guido Sanguinetti

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control.

Rhiannon Michelmore, Matthew Wicker, Luca Laurenti, Luca Cardelli, Yarin Gal, Marta Kwiatkowska

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019

Statistical Guarantees for the Robustness of Bayesian Neural Networks.

Luca Cardelli, Marta Kwiatkowska, Luca Laurenti, Nicola Paoletti, Andrea Patane, Matthew Wicker

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Robustness of 3D Deep Learning in an Adversarial Setting.

Matthew Wicker, Marta Kwiatkowska

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Efficient Learning of Optimal Markov Network Topology with k-Tree Modeling.

Liang Ding, Di Chang, Russell L. Malmberg, Aaron Martínez, David Robinson, Matthew Wicker, Hongfei Yan, Liming Cai

CoRR, 2018

Feature-Guided Black-Box Safety Testing of Deep Neural Networks.

Matthew Wicker, Xiaowei Huang, Marta Kwiatkowska

Proceedings of the Tools and Algorithms for the Construction and Analysis of Systems, 2018