Refined Pinsker's and Reverse Pinsker's Inequalities for Probability Distributions of Different Dimensions. - Michele Caprio (IEEE Access, 2022)

Dynamic precise and imprecise probability kinematics. - Michele Caprio; Ruobin Gong (ISIPTA, 2023)

Constriction for sets of probabilities. - Michele Caprio; Teddy Seidenfeld (ISIPTA, 2023)

Is the volume of a credal set a good measure for epistemic uncertainty? - Yusuf Sale; Michele Caprio; Eyke Hüllermeier (UAI, 2023)

Concentration Inequalities and Optimal Number of Layers for Stochastic Deep Neural Networks. - Michele Caprio; Sayan Mukherjee 001 (IEEE Access, 2023)

Imprecise Bayesian Neural Networks. - Michele Caprio; Souradeep Dutta; Kuk Jin Jang; Vivian Lin; Radoslav Ivanov; Oleg Sokolsky; Insup Lee 001 (CoRR, 2023)

Take Me Home: Reversing Distribution Shifts using Reinforcement Learning. - Vivian Lin; Kuk Jin Jang; Souradeep Dutta; Michele Caprio; Oleg Sokolsky; Insup Lee 001 (CoRR, 2023)

Using Semantic Information for Defining and Detecting OOD Inputs. - Ramneet Kaur; Xiayan Ji; Souradeep Dutta; Michele Caprio; Yahan Yang; Elena Bernardis; Oleg Sokolsky; Insup Lee 001 (CoRR, 2023)

Zero-shot Task Preference Addressing Enabled by Imprecise Bayesian Continual Learning. - Pengyuan Lu; Michele Caprio; Eric Eaton; Insup Lee 001 (CoRR, 2023)

Ergodic theorems for dynamic imprecise probability kinematics. - Michele Caprio; Sayan Mukherjee 001 (Int. J. Approx. Reason., 2023)

A Novel Bayes' Theorem for Upper Probabilities. - Michele Caprio; Yusuf Sale; Eyke Hüllermeier; Insup Lee 001 (Epi UAI, 2024)

Second-Order Uncertainty Quantification: A Distance-Based Approach. - Yusuf Sale; Viktor Bengs; Michele Caprio; Eyke Hüllermeier (ICML, 2024)

DC4L: Distribution shift recovery via data-driven control for deep learning models. - Vivian Lin; Kuk Jin Jang; Souradeep Dutta; Michele Caprio; Oleg Sokolsky; Insup Lee 001 (L4DC, 2024)

Credal Learning Theory. - Michele Caprio; Maryam Sultana; Eleni Elia; Fabio Cuzzolin (NeurIPS, 2024)

Credal Bayesian Deep Learning. - Michele Caprio; Souradeep Dutta; Kuk Jin Jang; Vivian Lin; Radoslav Ivanov; Oleg Sokolsky; Insup Lee 001 (Trans. Mach. Learn. Res., 2024)

Distributionally Robust Statistical Verification with Imprecise Neural Networks. - Souradeep Dutta; Michele Caprio; Vivian Lin; Matthew Cleaveland; Kuk Jin Jang; Ivan Ruchkin; Oleg Sokolsky; Insup Lee 001 (HSCC, 2025)

Optimal transport for ε-contaminated credal sets. - Michele Caprio (ISIPTA, 2025)

Conformal prediction regions are imprecise highest density regions. - Michele Caprio; Yusuf Sale; Eyke Hüllermeier (ISIPTA, 2025)

Conformalized Credal Regions for Classification with Ambiguous Ground Truth. - Michele Caprio; David Stutz; Shuo Li; Arnaud Doucet (Trans. Mach. Learn. Res., 2025)

TAR: Teacher-Aligned Representations via Contrastive Learning for Quadrupedal Locomotion. - Amr Mousa; Neil Karavis; Michele Caprio; Wei Pan 004; Richard Allmendinger 001 (CoRR, 2025)

Integral Imprecise Probability Metrics. - Siu Lun Chau; Michele Caprio; Krikamol Muandet (CoRR, 2025)

Epistemic Errors of Imperfect Multitask Learners When Distributions Shift. - Sabina J. Sloman; Michele Caprio; Samuel Kaski (CoRR, 2025)

The Joys of Categorical Conformal Prediction. - Michele Caprio (CoRR, 2025)