research
∙
01/12/2022
PyHHMM: A Python Library for Heterogeneous Hidden Markov Models
We introduce PyHHMM, an object-oriented open-source Python implementatio...
share
research
∙
10/26/2021
Modular Gaussian Processes for Transfer Learning
We present a framework for transfer learning based on modular variationa...
research
∙
08/23/2021
Regularizing Transformers With Deep Probabilistic Layers
Language models (LM) have grown with non-stop in the last decade, from s...
research
∙
07/13/2021
Deep Autoregressive Models with Spectral Attention
Time series forecasting is an important problem across many domains, pla...
research
∙
03/12/2021
Medical data wrangling with sequential variational autoencoders
Medical data sets are usually corrupted by noise and missing data. These...
research
∙
12/15/2020
Unsupervised Learning of Global Factors in Deep Generative Models
We present a novel deep generative model based on non i.i.d. variational...
research
∙
11/14/2020
Passive detection of behavioral shifts for suicide attempt prevention
More than one million people commit suicide every year worldwide. The co...
research
∙
10/06/2020
Recyclable Gaussian Processes
We present a new framework for recycling independent variational approxi...
research
∙
07/24/2020
Multinomial Sampling for Hierarchical Change-Point Detection
Bayesian change-point detection, together with latent variable models, a...
research
∙
06/04/2020
Robust Sampling in Deep Learning
Deep learning requires regularization mechanisms to reduce overfitting a...
research
∙
11/06/2019
Deep Sequential Models for Suicidal Ideation from Multiple Source Data
This article presents a novel method for predicting suicidal ideation fr...
research
∙
10/31/2019
Continual Multi-task Gaussian Processes
We address the problem of continual learning in multi-task Gaussian proc...
research
∙
10/22/2019
Continual Learning for Infinite Hierarchical Change-Point Detection
Change-point detection (CPD) aims to locate abrupt transitions in the ge...
research
∙
09/11/2018
Change-Point Detection on Hierarchical Circadian Models
This paper addresses the problem of change-point detection on sequences ...
research
∙
05/19/2018
Heterogeneous Multi-output Gaussian Process Prediction
We present a novel extension of multi-output Gaussian processes for hand...
research
∙
07/18/2014
Bayesian Nonparametric Crowdsourcing
Crowdsourcing has been proven to be an effective and efficient tool to a...
research
∙
12/31/2012
