Research

[23] Caprio, M., et al. (2024+). Imprecise Evidential Calssification.

[24] Caprio, M., Sale, Y., Lee, I., Hüllermeier, E. (2024+). Conformal Construction of Credal Sets.

[25] Caprio, M., Martin, R. (2024+). Belief-Infused Conformal Prediction.

[26] Rodemann, J., Caprio, M., Marquard, A., Augustin, T. (2024+). Lego Laplace: Fast and Modular Computation of Highest Density Regions in Bayesian Neural Networks.

[27] Caprio, M. (2024+). A Credal Approach to Quantum Conformal Prediction.

[28] Caprio, M. (2024+). Evidential-Bayes Inference and its Application to Continual Learning

[29] Tumu, N., Jang, K. J., Caprio, M. (2024+). Physics Constrained Credal Bayesian Deep Learning.

[30] Caprio, M. (2024+). Robust Variational Inference via Imprecise Probabilities.

[31] Caprio, M., Dobriban, E., Li, S. (2024+). Countering Label Shifts: an Imprecise PAC-Bayes Procedure.

Preprints

[16] Caprio, M., Mukherjee, S. (2023). Finite Mixture Models: a Bridge with Stochastic Geometry and Choquet Theory. ArXiV.

[17] Kaur, R., et al. (2023) Using Semantic Information for Defining and Detecting OOD Inputs. ArXiV.

[18] Lu, E., Caprio, M., Eaton, E., Lee, I. (2024). IBCL: Zero-shot Model Generation for Task Trade-offs in Continual Learning. ArXiV.

[19] Dutta, S., et al. (2024). Distributionally Robust Statistical Verification with Imprecise Neural Networks. ArXiV.

[20] Caprio, M. (2024). Imprecise Markov Semigroups and their Ergodicity. ArXiV.

[21] Caprio, M. (2024). Optimal Transport for ε-Contaminated Credal Sets. ArXiV.

[22] Caprio, M., et al. (2024+). Conformalized Credal Regions for Classification with Ambiguous Ground Truth. ArXiV.

Working Papers

Publications

[1] Leonetti, P., Caprio, M. (2021). Turnpike in Infinite Dimension. Canadian Mathematical Bulletin.

[2] Caprio, M., Aveni, A., Mukherjee, S. (2022). Concerning Three Classes of Non-Diophantine Arithmetics. Involve.

[3] Caprio, M., Aveni, A., Mukherjee, S. (2022). Concerning Two Classes of Non-Diophantine Arithmetics. Proceedings of IS4SI 2021.

[4] Caprio, M. (2022). Refined Pinsker's and Reverse Pinsker's Inequalities for Probability Distributions of Different Dimensions. IEEE Acc.

[5] Caprio, M., Mukherjee, S. (2022). Ergodic Theorems for Dynamic Imprecise Probability Kinematics. IJAR.

[6] Caprio, M., Mukherjee, S. (2023). Concentration Inequalities and Optimal Number of Layers of Stochastic Neural Networks. IEEE Acc.

[7] Caprio, M., Gong, R. (2023). Dynamic Precise and Imprecise Probability Kinematics. ISIPTA 2023.

[8] Caprio, M., Seidenfeld, T. (2023). Constriction for Sets of Probabilities. ISIPTA 2023.

[9] Sale, Y., Caprio, M., Hüllermeier, E. (2023). Is the Volume of a Credal Set a Good Measure for Epistemic Uncertainty? UAI 2023.

[10] Caprio, M., Mukherjee, S. (2023). Extended Probabilities and their Application to Statistical Inference. In "Understanding Information and Its Role as a Tool: In Memory of Mark Burgin", World Scientific publisher.

[11] Caprio, M., Sale, Y., Hullermeier, E., Lee, I. (2023). A Novel Bayes' Theorem for Upper Probabilities. E-pi UAI 2023.

[12] Lin, V., et al. (2024). DC4L: Distribution Shift Recovery via Data-Driven Control for Deep Learning Models. L4DC 2024.

[13] Sale, Y., Bengs, V., Caprio, M., Hüllermeier, E. (2024). Second-Order Uncertainty Quantification: a Distance-Based Approach. ICML 2024.

[14] Caprio, M., et al. (2024). Credal Bayesian Deep Learning. TMLR.

[15] Caprio, M., Sultana, M., Elia, E., Cuzzolin, F. (2024). Credal Learning Theory. NeurIPS 2024.