Publications
This is home for my research publications
Scaling Laws for Uncertainty in Deep Learning
Uncertainty Quantification
Bayesian Deep Learning
Scaling Laws
Machine Learning Theory
Think2SQL: Reinforce LLM Reasoning Capabilities for Text2SQL
Large Language Models
Text-to-SQL
Reinforcement Learning
Reasoning
From predictions to confidence intervals: an empirical study of conformal prediction methods for in-context learning
Large Language Models
Uncertainty Quantification
Transformers
Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation
Diffusion Models
Autonomous Driving
Trajectory Prediction
Controllable Generation
On permutation symmetries in Bayesian neural network posteriors: a variational perspective
Bayesian Deep Learning
Variational Inference
Optimization
Loss Landscapes
Permutation Symmetries
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