33 citations · 39 across the 3 of their papers we have counts for
5 papers
Enhancing Causal Estimation through Unlabeled Offline Data
Ron Teichner, Ron Meir, Danny Eitan
Consider a situation where a new patient arrives in the Intensive Care Unit (ICU) and is monitored by multiple sensors. We wish to assess relevant unmeasured physiological variable…
Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding
Sana Tonekaboni, Danny Eytan, Anna Goldenberg
Time series are often complex and rich in information but sparsely labeled and therefore challenging to model. In this paper, we propose a self-supervised framework for learning ge…
About Explicit Variance Minimization: Training Neural Networks for Medical Imaging With Limited Data Annotations
Dmitrii Shubin, Danny Eytan, Sebastian D. Goodfellow
Self-supervised learning methods for computer vision have demonstrated the effectiveness of pre-training feature representations, resulting in well-generalizing Deep Neural Network…
Using Deep Networks for Scientific Discovery in Physiological Signals
Tom Beer, Bar Eini-Porat, Sebastian Goodfellow +2
Deep neural networks (DNN) have shown remarkable success in the classification of physiological signals. In this study we propose a method for examining to what extent does a DNN's…
Generative ODE Modeling with Known Unknowns
Ori Linial, Neta Ravid, Danny Eytan +1
In several crucial applications, domain knowledge is encoded by a system of ordinary differential equations (ODE), often stemming from underlying physical and biological processes.…