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How to design a dataset compliant with an ML-based system ODD?, , , , , , , , , and 1 other author(s). CoRR, (2024)PUNCC: a Python Library for Predictive Uncertainty Calibration and Conformalization., , and . COPA, volume 204 of Proceedings of Machine Learning Research, page 582-601. PMLR, (2023)Deep Sturm-Liouville: From Sample-Based to 1D Regularization with Learnable Orthogonal Basis Functions., , , and . CoRR, (April 2025)Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure., , and . CoRR, (2022)Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models., , , , , and . CoRR, (May 2025)DP-SGD Without Clipping: The Lipschitz Neural Network Way., , , , , , , , and . CoRR, (2023)CRAFT: Concept Recursive Activation FacTorization for Explainability., , , , , , , and . CVPR, page 2711-2721. IEEE, (2023)Influenciæ: A Library for Tracing the Influence Back to the Data-Points., , , and . xAI (4), volume 2156 of Communications in Computer and Information Science, page 193-204. Springer, (2024)Efficient circuit implementation for coined quantum walks on binary trees and application to reinforcement learning., , and . SEC, page 436-443. IEEE, (2022)Object Detection with Probabilistic Guarantees: A Conformal Prediction Approach., , , , , and . SAFECOMP Workshops, volume 13415 of Lecture Notes in Computer Science, page 316-329. Springer, (2022)