activity
20182023
most citedSimple Contrastive Representation Learning for Time Series Forecasting

9 citations · 19 across the 5 of their papers we have counts for

collaborators
Showing cs.LGShow all

5 papers · 1 filter

cs.LG2023★ 9 cited

Simple Contrastive Representation Learning for Time Series Forecasting

Xiaochen Zheng, Xingyu Chen, Manuel Schürch +3

Contrastive learning methods have shown an impressive ability to learn meaningful representations for image or time series classification. However, these methods are less effective…

cs.LG2023★ 1 cited

Exploratory Analysis of Federated Learning Methods with Differential Privacy on MIMIC-III

Aron N. Horvath, Matteo Berchier, Farhad Nooralahzadeh +2

Background: Federated learning methods offer the possibility of training machine learning models on privacy-sensitive data sets, which cannot be easily shared. Multiple regulations…

cs.LG2020★ 8 cited

Patient Similarity Analysis with Longitudinal Health Data

Ahmed Allam, Matthias Dittberner, Anna Sintsova +2

Healthcare professionals have long envisioned using the enormous processing powers of computers to discover new facts and medical knowledge locked inside electronic health records.…

cs.LG2019

AutoDiscern: Rating the Quality of Online Health Information with Hierarchical Encoder Attention-based Neural Networks

Laura Kinkead, Ahmed Allam, Michael Krauthammer

Patients increasingly turn to search engines and online content before, or in place of, talking with a health professional. Low quality health information, which is common on the i…

cs.LG2018★ 1 cited

Neural networks versus Logistic regression for 30 days all-cause readmission prediction

Ahmed Allam, Mate Nagy, George Thoma +1

Heart failure (HF) is one of the leading causes of hospital admissions in the US. Readmission within 30 days after a HF hospitalization is both a recognized indicator for disease p…