We introduce PyHHMM, an object-oriented open-source Python implementatio...
We present a framework for transfer learning based on modular variationa...
Language models (LM) have grown with non-stop in the last decade, from
s...
Time series forecasting is an important problem across many domains, pla...
Medical data sets are usually corrupted by noise and missing data. These...
We present a novel deep generative model based on non i.i.d. variational...
More than one million people commit suicide every year worldwide. The co...
We present a new framework for recycling independent variational
approxi...
Bayesian change-point detection, together with latent variable models, a...
Deep learning requires regularization mechanisms to reduce overfitting a...
This article presents a novel method for predicting suicidal ideation fr...
We address the problem of continual learning in multi-task Gaussian proc...
Change-point detection (CPD) aims to locate abrupt transitions in the
ge...
This paper addresses the problem of change-point detection on sequences ...
We present a novel extension of multi-output Gaussian processes for hand...
Crowdsourcing has been proven to be an effective and efficient tool to
a...
This technical note considers the problems of blind sparse learning and
...