Matthew Wicker

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 38

Top Topics

Efficient Learning

Bayesian Inference

Top Venues

Publications

Philip Sosnin, Mark Niklas Müller, Maximilian Baader, Calvin Tsay, Matthew Wicker
Certified Robustness to Data Poisoning in Gradient-Based Training. CoRR (2024)
Matthew Wicker, Philip Sosnin, Adrianna Janik, Mark N. Müller, Adrian Weller, Calvin Tsay
Certificates of Differential Privacy and Unlearning for Gradient-Based Training. CoRR (2024)
Matthew Wicker, Luca Laurenti, Andrea Patane, Nicola Paoletti, Alessandro Abate, Marta Kwiatkowska
Probabilistic reach-avoid for Bayesian neural networks. Artif. Intell. 334 (2024)
Matthew Wicker, Vihari Piratla, Adrian Weller
Certification of Distributional Individual Fairness. NeurIPS (2023)
Juyeon Heo, Vihari Piratla, Matthew Wicker, Adrian Weller
Use perturbations when learning from explanations. NeurIPS (2023)
Matthew Wicker, Luca Laurenti, Andrea Patane, Nicola Paoletti, Alessandro Abate, Marta Kwiatkowska
Probabilistic Reach-Avoid for Bayesian Neural Networks. CoRR (2023)
Alice Doherty, Matthew Wicker, Luca Laurenti, Andrea Patane
Individual Fairness in Bayesian Neural Networks. CoRR (2023)
Matthew Wicker, Andrea Patane, Luca Laurenti, Marta Kwiatkowska
Adversarial Robustness Certification for Bayesian Neural Networks. CoRR (2023)
Matthew Wicker, Juyeon Heo, Luca Costabello, Adrian Weller
Robust Explanation Constraints for Neural Networks. ICLR (2023)
Matthew Wicker, Vihari Piratla, Adrian Weller
Certification of Distributional Individual Fairness. CoRR (2023)
Juyeon Heo, Vihari Piratla, Matthew Wicker, Adrian Weller
Robust Learning from Explanations. CoRR (2023)
Elias Benussi, Andrea Patane, Matthew Wicker, Luca Laurenti, Marta Kwiatkowska
Individual Fairness Guarantees for Neural Networks. CoRR (2022)
Benjie Wang, Matthew Wicker, Marta Kwiatkowska
Tractable Uncertainty for Structure Learning. CoRR (2022)
Matthew Wicker, Juyeon Heo, Luca Costabello, Adrian Weller
Robust Explanation Constraints for Neural Networks. CoRR (2022)
Emanuele La Malfa, Matthew Wicker, Marta Kiatkowska
Emergent Linguistic Structures in Neural Networks are Fragile. CoRR (2022)
Luca Bortolussi, Ginevra Carbone, Luca Laurenti, Andrea Patane, Guido Sanguinetti, Matthew Wicker
On the Robustness of Bayesian Neural Networks to Adversarial Attacks. CoRR (2022)
Benjie Wang, Matthew Wicker, Marta Kwiatkowska
Tractable Uncertainty for Structure Learning. ICML (2022)
Elias Benussi, Andrea Patanè, Matthew Wicker, Luca Laurenti, Marta Kwiatkowska
Individual Fairness Guarantees for Neural Networks. IJCAI (2022)
Matthew Wicker, Luca Laurenti, Andrea Patane, Zhoutong Chen, Zheng Zhang, Marta Kwiatkowska
Bayesian Inference with Certifiable Adversarial Robustness. CoRR (2021)
Matthew Wicker, Luca Laurenti, Andrea Patane, Zhuotong Chen, Zheng Zhang, Marta Kwiatkowska
Bayesian Inference with Certifiable Adversarial Robustness. AISTATS (2021)
Matthew Wicker, Luca Laurenti, Andrea Patane, Nicola Paoletti, Alessandro Abate, Marta Kwiatkowska
Certification of Iterative Predictions in Bayesian Neural Networks. CoRR (2021)
Matthew Wicker, Luca Laurenti, Andrea Patane, Nicola Paoletti, Alessandro Abate, Marta Kwiatkowska
Certification of iterative predictions in Bayesian neural networks. UAI (2021)
Min Wu, Matthew Wicker, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska
A game-based approximate verification of deep neural networks with provable guarantees. Theor. Comput. Sci. 807 (2020)
Matthew Wicker, Luca Laurenti, Andrea Patane, Marta Kwiatkowska
Probabilistic Safety for Bayesian Neural Networks. CoRR (2020)
Ginevra Carbone, Matthew Wicker, Luca Laurenti, Andrea Patane, Luca Bortolussi, Guido Sanguinetti
Robustness of Bayesian Neural Networks to Gradient-Based Attacks. CoRR (2020)
Ginevra Carbone, Matthew Wicker, Luca Laurenti, Andrea Patané, Luca Bortolussi, Guido Sanguinetti
Robustness of Bayesian Neural Networks to Gradient-Based Attacks. NeurIPS (2020)
Matthew Yuan, Matthew Wicker, Luca Laurenti
Gradient-Free Adversarial Attacks for Bayesian Neural Networks. CoRR (2020)
Matthew Wicker, Luca Laurenti, Andrea Patane, Marta Kwiatkowska
Probabilistic Safety for Bayesian Neural Networks. UAI (2020)
Rhiannon Michelmore, Matthew Wicker, Luca Laurenti, Luca Cardelli, Yarin Gal, Marta Kwiatkowska
Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control. ICRA (2020)
Matthew Wicker, Marta Kwiatkowska
Robustness of 3D Deep Learning in an Adversarial Setting. CVPR (2019)
Rhiannon Michelmore, Matthew Wicker, Luca Laurenti, Luca Cardelli, Yarin Gal, Marta Kwiatkowska
Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control. CoRR (2019)
Matthew Wicker, Marta Kwiatkowska
Robustness of 3D Deep Learning in an Adversarial Setting. CoRR (2019)
Luca Cardelli, Marta Kwiatkowska, Luca Laurenti, Nicola Paoletti, Andrea Patane, Matthew Wicker
Statistical Guarantees for the Robustness of Bayesian Neural Networks. IJCAI (2019)
Luca Cardelli, Marta Kwiatkowska, Luca Laurenti, Nicola Paoletti, Andrea Patane, Matthew Wicker
Statistical Guarantees for the Robustness of Bayesian Neural Networks. CoRR (2019)
Liang Ding, Di Chang, Russell L. Malmberg, Aaron Martínez, David Robinson, Matthew Wicker, Hongfei Yan, Liming Cai
Efficient Learning of Optimal Markov Network Topology with k-Tree Modeling. CoRR (2018)
Min Wu, Matthew Wicker, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska
A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees. CoRR (2018)
Matthew Wicker, Xiaowei Huang, Marta Kwiatkowska
Feature-Guided Black-Box Safety Testing of Deep Neural Networks. TACAS (1) (2018)
Matthew Wicker, Xiaowei Huang, Marta Kwiatkowska
Feature-Guided Black-Box Safety Testing of Deep Neural Networks. CoRR (2017)