MCML - Past Events at the Munich Center for Machine Learning

11

Jun

Link to Veridical Data Science and PCS Uncertainty
Quantification

Colloquium • 11.06.2025 • LMU Department of Statistics and via zoom

4:15 pm - 5:45 pm

Veridical Data Science and PCS Uncertainty Quantification

Bin Yu, Berkeley

Data Science is central to Al and has driven most of the recent advances in biomedicine and beyond. Human judgment calls are ubiquitous at every step of the data science life cycle (DSLC): problem formulation, data cleaning, EDA, modeling, and reporting. Auch judgment calls are often responsible for the “dangers” of Al by creating a universe of …

Democratizing Methods

Jennifer Hill, New York University

The past few decades have seen an explosion in the development of freely available software to implement statistical methods and algorithms to help explore and analyze data. However, researchers tend to assume that releasing software packages implementing specific methods is sufficient for ensuring that the tools are adopted and used correctly. …

Epistemology and Theory of Machine Learning

Limits, Interpretability, and Knowledge in Modern AI

This is the second edition of the Epistemology and Theory of Machine Learning series started in 2023. The rapid rise and huge impact of methods in machine learning raises important philosophical questions. There is, in particular, an increasing interest in questions of epistemology: how exactly do machine learning methods contribute to the pursuit …