Publications
This is home for my research publications
The Initialization Determines Whether In-Context Learning Is Gradient Descent
Large Language Models
Deep Learning Theory
Scaling Laws for Uncertainty in Deep Learning
Uncertainty Quantification
Bayesian Deep Learning
Deep Learning Theory
From predictions to confidence intervals: an empirical study of conformal prediction methods for in-context learning
Large Language Models
Uncertainty Quantification
On permutation symmetries in Bayesian neural network posteriors: a variational perspective
Bayesian Deep Learning
Variational Inference
Deep Learning Theory
How Much is Enough? A Study on Diffusion Times in Score-based Generative Models
Diffusion Models
Generative Modeling
Continuous-Time Functional Diffusion Processes
Diffusion Models
Generative Modeling
Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations
Proceedings of The 24th International Conference on Artificial Intelligence and Statistics (AISTATS)
Gaussian Processes
Variational Inference
Bayesian Deep Learning
All You Need is a Good Functional Prior for Bayesian Deep Learning
Bayesian Deep Learning
Gaussian Processes
Variational Inference
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