83 citations · 225 across the 27 of their papers we have counts for
4 papers · 1 filter
Grouped Gaussian Processes for Solar Power Prediction
Astrid Dahl, Edwin V. Bonilla
We consider multi-task regression models where the observations are assumed to be a linear combination of several latent node functions and weight functions, which are both drawn f…
Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference
Louis C. Tiao, Edwin V. Bonilla, Fabio Ramos
We formalize the problem of learning interdomain correspondences in the absence of paired data as Bayesian inference in a latent variable model (LVM), where one seeks the underlyin…
Calibrating Deep Convolutional Gaussian Processes
Gia-Lac Tran, Edwin V. Bonilla, John P. Cunningham +2
The wide adoption of Convolutional Neural Networks (CNNs) in applications where decision-making under uncertainty is fundamental, has brought a great deal of attention to the abili…
Efficient Inference in Multi-task Cox Process Models
Virginia Aglietti, Theodoros Damoulas, Edwin Bonilla
We generalize the log Gaussian Cox process (LGCP) framework to model multiple correlated point data jointly. The observations are treated as realizations of multiple LGCPs, whose l…