Francesco Pozza

PostDoc in Statistics

[Daniele Durante @DanieleDurante2]

😎 For any, already-derived, symmetric approximation of a generic posterior distribution, we provide, at no additional optimization costs, a similarly-tractable, yet provably more accurate, skew-symmetric approximation! (https://t.co/6N7SrE4HC2) (with @FraPozza and @BotondSzabo6)

[Sirio Legramanti @SirioLegramanti]

Our paper "Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity" has been accepted by the Annals of Statistics! 🎉🎉🎉
Thanks to my coauthors @DanieleDurante2 and @PierreAlquier for sharing this amazing journey! 🙏
https://t.co/YfsW1Qvqf2

[Daniele Durante @DanieleDurante2]

🤩 Congratulations to my former PhD student @FraPozza who received the Laplace award 🏆 at #JSM2024, for the article "skewed Bernstein-von Mises theorem and skew-modal approximations" (https://t.co/mFC7dhSz8O) (recently accepted for publication in the Annals of Statistics ‼️)

[Daniele Durante @DanieleDurante2]

The skewed Bernstein-von Mises theorem is online https://t.co/Yac4NwZ0LV. With @FraPozza and @BotondSzabo6 we derive a new limiting law given by tractable generalized skew-normals that remarkably improves the convergence rate (and practical accuracy) of the classical BvM result!