2 citations · 3 across the 4 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
stat.ML2018
Discretely Relaxing Continuous Variables for tractable Variational Inference
Trefor W. Evans, Prasanth B. Nair
We explore a new research direction in Bayesian variational inference with discrete latent variable priors where we exploit Kronecker matrix algebra for efficient and exact computa…
stat.ML2018
Exploiting Structure for Fast Kernel Learning
Trefor W. Evans, Prasanth B. Nair
We propose two methods for exact Gaussian process (GP) inference and learning on massive image, video, spatial-temporal, or multi-output datasets with missing values (or "gaps") in…
stat.ML2018
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)
Trefor W. Evans, Prasanth B. Nair
We introduce a kernel approximation strategy that enables computation of the Gaussian process log marginal likelihood and all hyperparameter derivatives in time. O…