240 citations · 503 across the 31 of their papers we have counts for
4 papers · 1 filter
ML-based Flood Forecasting: Advances in Scale, Accuracy and Reach
Sella Nevo, Gal Elidan, Avinatan Hassidim +4
Floods are among the most common and deadly natural disasters in the world, and flood warning systems have been shown to be effective in reducing harm. Yet the majority of the worl…
HydroNets: Leveraging River Structure for Hydrologic Modeling
Zach Moshe, Asher Metzger, Gal Elidan +3
Accurate and scalable hydrologic models are essential building blocks of several important applications, from water resource management to timely flood warnings. However, as the cl…
DNF-Net: A Neural Architecture for Tabular Data
Ami Abutbul, Gal Elidan, Liran Katzir +1
A challenging open question in deep learning is how to handle tabular data. Unlike domains such as image and natural language processing, where deep architectures prevail, there is…
Convex Nonparanormal Regression
Yonatan Woodbridge, Gal Elidan, Ami Wiesel
Quantifying uncertainty in predictions or, more generally, estimating the posterior conditional distribution, is a core challenge in machine learning and statistics. We introduce C…