SEMINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO

Venerdì 05/06/2026, presso il Collegio Carlo Alberto, in Piazza Arbarello 8, Torino, si terrà il seguente seminario:

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12.00-13.00

Speaker: Sara WADE (UNIVERSITY OF EDINBURGH)

Title: Explainable Bayesian learning

Abstract: The Bayesian approach is widely valued for its principled treatment of uncertainty and its ability to propagate this uncertainty to predictions. However, advances in modeling and data acquisition have led to posterior distributions defined over increasingly complicated parameter spaces, making them difficult to interpret and summarize. This challenge extends to predictive distributions, which in modern applications may reside on non‑standard spaces such as partitions, sequences, or graphs. In this work, we develop tools for explaining and summarizing non‑standard posterior and predictive distributions arising in Bayesian learning. We illustrate the core ideas in context of clustering, utilizing the Wasserstein distance to obtain a succint, discrete summary of posterior distributions on the space of partitions. We further outline extensions to clustering with clutter and variable selection, and demonstrate how the proposed tools remain useful beyond the Bayesian setting when data itself is uncertain.

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Sarà possibile seguire il seminario anche in streaming: chiunque volesse collegarsi è pregato di inviare un’email a matteo.giordano@unito.it

Il webinar è organizzato dalla "de Castro" Statistics Initiative (www.carloalberto.org/stats) in collaborazione con il Collegio Carlo Alberto.

Cordiali saluti,