Bayesian Meta-Learning Through Variational Gaussian Processes

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Deep Learning vmgp
Overview

vmgp

This is the repository of Vivek Myers and Nikhil Sardana for our CS 330 final project, Bayesian Meta-Learning Through Variational Gaussian Processes.

Full paper: TBD

summary of results

Above: Predictions (bottom row) and posterior predictive distribution densities (for the single red testing point, top row) from each model on a 5·floor(z) latent function task. VMGP is able to predict a multimodal mixture of point distributions to model its uncertainty, outperforming the other, less expressive methods.

prediction examples

Above: Sinusoid Regression Examples. Columns, from left: EMAML, AlPaCA, DKT, VMGP (ours). Each row shows an example test task from a different variant of the regression environment. Rows, from top: standard sinusoids, high frequency sinusoids, out of range testing, and tangent functions.

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Owner
Vivek Myers
Vivek Myers
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