3 papers
stat.ML2025
Sparse Gaussian Processes: Structured Approximations and Power-EP Revisited
Thang D. Bui, Michalis K. Titsias
Inducing-point-based sparse variational Gaussian processes have become the standard workhorse for scaling up GP models. Recent advances show that these methods can be improved by i…
cs.LG2024
Improving Uncertainty Quantification in Large Language Models via Semantic Embeddings
Yashvir S. Grewal, Edwin V. Bonilla, Thang D. Bui
Accurately quantifying uncertainty in large language models (LLMs) is crucial for their reliable deployment, especially in high-stakes applications. Current state-of-the-art method…
stat.ML2024
Likelihood approximations via Gaussian approximate inference
Thang D. Bui
Non-Gaussian likelihoods are essential for modelling complex real-world observations but pose significant computational challenges in learning and inference. Even with Gaussian pri…