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No Free Lunch in Inference

January 31, 2022

Speakers:

Benjamin Bolker

Statistical methods can target exploration, prediction, or inference.

How are the Causes of Complex Disease Distributed in the Human Genome

February 4, 2022

Speakers:

David Balding

The advent of very large, richly-phenotyped and high-quality human genomics datasets, together with the development of models that allow joint anal

Spatial Skills in STEM with a Focus on Computing and Diversity

January 24, 2022

Speakers:

Michael Liut

Numerous correlational studies have demonstrated the link between spatial skills and success in STEM.

Multi-Phenotype Analysis in Human Genetic Studies

January 10, 2022

Speakers:

Hugues Aschard

During the past 15 years genome-wide association studies (GWAS) have been conducted on thousands of human phenotypes, providing an overview of the

Some Insights from Doubly Infinite Neural Networks

December 9, 2021

Speakers:

Soufiane Hayou, National University of Singapore

The theoretical analysis of infinite-width neural networks has led to many interesting practical results (choice of initialization schemes, choice

When Geometry and Statistics Meet Cosmology: the Challenge of Detecting Cosmic Webs.

December 13, 2021

Speakers:

Yen-Chi Chen

Matter in our Universe tends to aggregate around lower-dimension structures, weaving our Universe into a web-like structure known as the cosmic web

The Rigorous and Human Life of Data

December 6, 2021

Speakers:

Cecilia Aragon

Very often, the words “rigorous” and “human-centered” have been used as opposites in technical fields, with the implication that a focus on human a

Policy Questions, Messy Data: Three Approaches to Turning Messy Data Into Information for Public Policy

November 29, 2021

Speakers:

Krista Gile

This talk describes 3 projects demonstrating the development of statistical methods to use messy data on people to draw conclusions for public heal

A Modern Take on Huber Regression

December 2, 2021

Speakers:

Po-Ling Loh, University of Cambridge

In the first part of the talk, we discuss the use of a penalized Huber M-estimator for high-dimensional linear regression.

Diffusion Schrödinger Bridges with Applications to Score-Based Generative Modelling

November 25, 2021

Speakers:

Arnaud Doucet, University of Oxford

Progressively applying Gaussian noise transforms complex data distributions to approximately Gaussian.

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