Probabilistic lenses (Spring 2025)

Abstract

🔭 This (somewhat experimental) lecture explores how probability connects mathematical theory with our understanding of the world - from foundational ideas to practical modeling.

📐 We’ll examine mathematical foundations like entropy and its various interpretations and applications, Dutch Book theorems, von Neumann-Morgenstern axioms, relationships with high-dimensional spaces, connections to machine learning, statistics, forecasting, Bayesian inference, and more.

🧭 Instead of focusing deeply on a particular topic, the lectures will explore various ideas that we find insightful, drawing inspiration from information theory, Bayesian statistics, and some LessWrong-inspired aesthetics of modeling and understanding the world through probability.

📚 A basic understanding of probability is assumed (e.g. Probability 1). Fondness of a probabilistic viewpoint is recommended. Some familiarity with related fields will help you get more from the lecture but it is not required.

Bookkeeping

The lecture takes place on Thursday, 15:40 in S5. In SIS, it is registered as Chapters from complexity theory II. It is for 4 credits.

Lectures

TBD