Louis Tiao

PhD Thesis Acknowledgements (Unabridged)

Probabilistic Machine Learning in the Age of Deep Learning: New Perspectives for Gaussian Processes, Bayesian Optimization and Beyond (PhD Thesis)

One paper accepted to ICML2023

Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes

Efficient Cholesky decomposition of low-rank updates

Batch Bayesian Optimisation via Density-ratio Estimation with Guarantees

One paper accepted to NeurIPS2022

BORE: Bayesian Optimization by Density-Ratio Estimation

A Primer on Pólya-gamma Random Variables - Part II: Bayesian Logistic Regression

Exploring the Binance API in Python - Part II: Recent and Historical Trades

An Illustrated Guide to the Knowledge Gradient Acquisition Function

Exploring the Binance API in Python - Part I: The Order Book

Welcome to Hugo Blox Builder, the website builder for Hugo

Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings

Model-based Asynchronous Hyperparameter and Neural Architecture Search

A Handbook for Sparse Variational Gaussian Processes

Writing technical content in Markdown

Display Jupyter Notebooks with Academic

Slides

Density Ratio Estimation for KL Divergence Minimization between Implicit Distributions

Building Probability Distributions with the TensorFlow Probability Bijector API

Contributed Talk: Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference

Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference

Example Project

Fourier decomposition of Gaussian processes III

A Tutorial on Variational Autoencoders with a Concise Keras Implementation

NumPy mgrid vs. meshgrid