43 citations · 139 across the 20 of their papers we have counts for
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Spectral Mixture Kernels for Multi-Output Gaussian Processes
Gabriel Parra, Felipe Tobar
Early approaches to multiple-output Gaussian processes (MOGPs) relied on linear combinations of independent, latent, single-output Gaussian processes (GPs). This resulted in cross-…
Recovering Latent Signals from a Mixture of Measurements using a Gaussian Process Prior
Felipe Tobar, Gonzalo Rios, Tomás Valdivia +1
In sensing applications, sensors cannot always measure the latent quantity of interest at the required resolution, sometimes they can only acquire a blurred version of it due the s…
Improving Sparsity in Kernel Adaptive Filters Using a Unit-Norm Dictionary
Felipe Tobar
Kernel adaptive filters, a class of adaptive nonlinear time-series models, are known by their ability to learn expressive autoregressive patterns from sequential data. However, for…
Initialising Kernel Adaptive Filters via Probabilistic Inference
Iván Castro, Cristóbal Silva, Felipe Tobar
We present a probabilistic framework for both (i) determining the initial settings of kernel adaptive filters (KAFs) and (ii) constructing fully-adaptive KAFs whereby in addition t…