1 citations · 1 across the 1 of their papers we have counts for
4 papers
Universal approximation and model compression for radial neural networks
Iordan Ganev, Twan van Laarhoven, Robin Walters
We introduce a class of fully-connected neural networks whose activation functions, rather than being pointwise, rescale feature vectors by a function depending only on their norm.…
Multi-Output Convolution Spectral Mixture for Gaussian Processes
Kai Chen, Twan van Laarhoven, Perry Groot +2
Multi-output Gaussian processes (MOGPs) are an extension of Gaussian Processes (GPs) for predicting multiple output variables (also called channels, tasks) simultaneously. In this…
Multitask Gaussian Process with Hierarchical Latent Interactions
Kai Chen, Twan van Laarhoven, Elena Marchiori +2
Multitask Gaussian process (MTGP) is powerful for joint learning of multiple tasks with complicated correlation patterns. However, due to the assembling of additive independent lat…
Unsupervised Domain Adaptation with Random Walks on Target Labelings
Twan van Laarhoven, Elena Marchiori
Unsupervised Domain Adaptation (DA) is used to automatize the task of labeling data: an unlabeled dataset (target) is annotated using a labeled dataset (source) from a related doma…