The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks
Authors: Ziquan Liu, Yufei Cui, Yan Yan, Yi Xu, Xiangyang Ji, Xue Liu, Antoni B. Chan | Published: 2024-05-14
不確実性の定量化
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks
Authors: Yunzhen Feng, Tim G. J. Rudner, Nikolaos Tsilivis, Julia Kempe | Published: 2024-04-27
Conformal Predictions for Probabilistically Robust Scalable Machine Learning Classification
Authors: Alberto Carlevaro, Teodoro Alamo Cantarero, Fabrizio Dabbene, Maurizio Mongelli | Published: 2024-03-15
Manipulating hidden-Markov-model inferences by corrupting batch data
Authors: William N. Caballero, Jose Manuel Camacho, Tahir Ekin, Roi Naveiro | Published: 2024-02-19
On the Impact of Uncertainty and Calibration on Likelihood-Ratio Membership Inference Attacks
Authors: Meiyi Zhu, Caili Guo, Chunyan Feng, Osvaldo Simeone | Published: 2024-02-16 | Updated: 2025-03-14
Uncertainty-Aware Hardware Trojan Detection Using Multimodal Deep Learning
Authors: Rahul Vishwakarma, Amin Rezaei | Published: 2024-01-15 | Updated: 2024-01-23
Risk-Aware and Explainable Framework for Ensuring Guaranteed Coverage in Evolving Hardware Trojan Detection
Authors: Rahul Vishwakarma, Amin Rezaei | Published: 2023-10-14
Random-Set Neural Networks (RS-NN)
Authors: Shireen Kudukkil Manchingal, Muhammad Mubashar, Kaizheng Wang, Keivan Shariatmadar, Fabio Cuzzolin | Published: 2023-07-11 | Updated: 2025-02-14
Who’s Afraid of Thomas Bayes?
Authors: Erick Galinkin | Published: 2021-07-30
Towards Improving the Trustworthiness of Hardware based Malware Detector using Online Uncertainty Estimation
Authors: Harshit Kumar, Nikhil Chawla, Saibal Mukhopadhyay | Published: 2021-03-21