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07/11/2022
A clinically motivated self-supervised approach for content-based image retrieval of CT liver images
Deep learning-based approaches for content-based image retrieval (CBIR) ...
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05/18/2022
The Kernelized Taylor Diagram
This paper presents the kernelized Taylor diagram, a graphical framework...
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03/17/2022
Mixing Up Contrastive Learning: Self-Supervised Representation Learning for Time Series
The lack of labeled data is a key challenge for learning useful represen...
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12/19/2021
RELAX: Representation Learning Explainability
Despite the significant improvements that representation learning via se...
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07/07/2021
On the Use of Time Series Kernel and Dimensionality Reduction to Identify the Acquisition of Antimicrobial Multidrug Resistance in the Intensive Care Unit
The acquisition of Antimicrobial Multidrug Resistance (AMR) in patients ...
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02/27/2020
A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs
A large fraction of the electronic health records (EHRs) consists of cli...
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07/10/2019
Time series cluster kernels to exploit informative missingness and incomplete label information
The time series cluster kernel (TCK) provides a powerful tool for analys...
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02/20/2019
Noisy multi-label semi-supervised dimensionality reduction
Noisy labeled data represent a rich source of information that often are...
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05/09/2018
Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders
Learning compressed representations of multivariate time series (MTS) fa...
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03/21/2018
An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples
A large fraction of the electronic health records consists of clinical m...
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11/17/2017
Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks
Clinical measurements that can be represented as time series constitute ...
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10/20/2017
Learning compressed representations of blood samples time series with missing data
Clinical measurements collected over time are naturally represented as m...
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04/03/2017