Yin Cheng Ng — accepted AI-conference papers

2018

Bayesian Semi-supervised Learning with Graph Gaussian Processes

Yin Cheng Ng, Nicolò Colombo, Ricardo Silva

NeurIPS 2018poster

We propose a data-efficient Gaussian process-based Bayesian approach to the semi-supervised learning problem on graphs. The proposed model shows extremely competitive performance when compared to the state-of-the-art graph neural networks on semi-supervised learning benchmark experiments, and outper…

Cited by 117 Source ↗PDF ↗code ↗Scholar ↗

2016

Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages

Yin Cheng Ng, Pawel M Chilinski, Ricardo Silva

NeurIPS 2016poster

Factorial Hidden Markov Models (FHMMs) are powerful models for sequential data but they do not scale well with long sequences. We propose a scalable inference and learning algorithm for FHMMs that draws on ideas from the stochastic variational inference, neural network and copula literatures. Unlike…

Cited by 19 Source ↗PDF ↗Scholar ↗