Workshop on Theory for Scalable, Modern Statistical Methods

The workshop aims to bring together researchers working on new directions in modern statistical problems, including scalable computation (both Bayesian and frequentist), uncertainty quantification, high-dimensional structured models, manifold estimation, non-linear inverse problems, causality, deep learning, etc.

5 APRIL 2023

 

9:30AM-10:15AM

Trade-Offs for Multiple Testing and Classification of Sparse Vectors

ISMAEL CASTILLO Sorbonne Université

10:15AM-11:00AM

Bayesian Sensitivity Analysis in Causal Analysis

AAD VAN DER VAART TU Delft

 

11:30AM-12:15PM

Early Stopping for L^2-Boosting in Sparse High-Dimensional Linear Models

BERNHARD STANKEWITZ Bocconi University

 

12:15PM-1:00PM

The Cost of Privacy and Bandwidth Constraints in Non-Parametric Distributed Hypothesis Testing

LASSE VUURSTEEN TU Delft

 

3:30PM-4:15PM

Posterior Contraction Rates for Stationary Gaussian Processes Priors on Compact Lie Groups and Their Homogeneous Spaces

PAUL ROSA University of Oxford

4:15PM-5:00PM

Bayes Meets Bernstein in Meta-Learning

BADR-EDDINECHÉRIEF-ABDELLATIF Sorbonne Université

5:30PM-6:15PM

Non-Parametric Estimation of Marginal Likelihood

OMIROS PAPASPILIOPOULOS Bocconi University

6 APRIL 2023

9:30AM-10:15AM

On Posterior Consistency in Non-Linear Data. Assimilation Problems with Gaussian Process Priors

RICHARD NICKL University of Cambridge

10:15AM-11:00AM

A Bernstein-Von Mises Theorem for the Calderón Problem with Piecewise Constant Conductivities

JAN BOHR University of Bonn

11:30AM-12:15PM

On Estimating Multidimensional Diffusion from Discrete Data

MARC HOFFMAN Université Paris Dauphine PSL

12:15PM-1:00PM

Neural Processes for Parametric Partial Differential Equations

IEVA KAZLAUSKAITE University of Cambridge 

3:30PM-4:15PM

Bayesian Targeted Inference in Semi-Parametric Models

JUDITH ROUSSEAU University of Oxford

4:15PM-5:00PM

Semi-Parametric Inference Using Fractional Posteriors

ALICE L’HUILLIER Sorbonne Université

5:30PM-6:15PM

Detection and Recovery of Sparse Signal Under Correlation

CHAO GAO University of Chicago

7 APRIL 2023

9:30AM-10:15AM

A Frequentist Analysis of Variational Gaussian Procces Regression with Inducing Points

DENNIS NIEMAN VU Amsterdam

10:15PM-11:00AM

Deep Horseshoe Gaussian Processes

THIBAULT RANDRIANARISOA Bocconi University

11:30AM-12:15PM

Adaptive Rates of Contraction with Heavy-Tailed Priors

SERGIOS AGAPIOU University of Cyprus

12:15PM-1:00PM

Bayesian Non-Parametric Intensity Estimation for Inhomogeneous Point Processes with Covariates

MATTEO GIORDANO University of Oxford

Organized by

Università Bocconi

BIDSA — Bocconi Institute for Data Science and Analytics

The workshop is sponsored by the ERC Starting Grant (no. 101041064) for the project: “BigBayesUQ: The missing story of Bayesian uncertainty quantification for big data”.