Louis Tiao — accepted AI-conference papers

2026

Empirical Gaussian Processes

Jihao Andreas Lin, Sebastian Ament, Louis Tiao, David Eriksson, Maximilian Balandat, Eytan Bakshy

ICML 2026poster

Gaussian processes (GPs) are powerful and widely used probabilistic regression models, but their effectiveness in practice is often limited by the choice of kernel function. This kernel function is typically handcrafted from a small set of standard functions, a process that requires expert knowledge…

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2020

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

Pantelis Elinas, Edwin V. Bonilla, Louis Tiao

NeurIPS 2020spotlight

We propose a framework that lifts the capabilities of graph convolutional networks (GCNs) to scenarios where no input graph is given and increases their robustness to adversarial attacks. We formulate a joint probabilistic model that considers a prior distribution over graphs along with a GCN-based…

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