21 citations · 21 across the 3 of their papers we have counts for
4 papers
Sintel: A Machine Learning Framework to Extract Insights from Signals
Sarah Alnegheimish, Dongyu Liu, Carles Sala +2
The detection of anomalies in time series data is a critical task with many monitoring applications. Existing systems often fail to encompass an end-to-end detection process, to fa…
Probabilistic Programming Bots in Intuitive Physics Game Play
Fahad Alhasoun, Sarah Alnegheimish, Joshua Tenenbaum
Recent findings suggest that humans deploy cognitive mechanism of physics simulation engines to simulate the physics of objects. We propose a framework for bots to deploy probabili…
Cardea: An Open Automated Machine Learning Framework for Electronic Health Records
Sarah Alnegheimish, Najat Alrashed, Faisal Aleissa +4
An estimated 180 papers focusing on deep learning and EHR were published between 2010 and 2018. Despite the common workflow structure appearing in these publications, no trusted an…
TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks
Alexander Geiger, Dongyu Liu, Sarah Alnegheimish +2
Time series anomalies can offer information relevant to critical situations facing various fields, from finance and aerospace to the IT, security, and medical domains. However, det…