Recent & Upcoming Talks

Keynote

Invited talk

Invited talk

Invited talk

Pretrained Transformers as In-Context Bayesian Learners: Implications for Uncertainty Quantification

Pretrained Transformers as In-Context Bayesian Learners: Implications for Uncertainty Quantification

Bayes-Filtered Transformers

Pretrained Transformers as In-Context Bayesian Learners: Implications for Uncertainty Quantification

A Principled Framework for Uncertainty Decomposition in TabPFN

Bayesian Predictive Inference and Transformers

Transformers as Bayesian Predictive Engines

What Is Prediction For? Turning Pre-Trained Transformers into Bayesian Engines

Dynamical versus Bayesian Transitions in a Toy Model of Superposition

What Is Prediction For? Turning Pre-Trained Transformers into Bayesian Engines

What’s Degeneracy Got to Do with It? Understanding Deep Neural Networks through Singular Learning Theory

Dynamical versus Bayesian Transitions in a Toy Model of Superposition

What’s Degeneracy Got to Do with It? Understanding Deep Neural Networks through Singular Learning Theory

Dynamical versus Bayesian Transitions in a Toy Model of Superposition

Dynamical versus Bayesian Phase Transitions in a Toy Model of Superposition

A Bayesian Model Selection Criterion for Better Fine-tuning

What’s Degeneracy Got to Do with It?

Quantifying degeneracy in singular models via the learning coefficient

Quantifying degeneracy in singular statistical models

What’s degeneracy got to do with it?

Quantifying degeneracy in singular models via the learning coefficient

Quantifying degeneracy in singular models via the learning coefficient

What’s degeneracy got to do with it?

Variational Bayesian Neural Networks via Singular Learning Theory