Search Results for author: Sella Nevo

Found 10 papers, 2 papers with code

On pseudo-absence generation and machine learning for locust breeding ground prediction in Africa

1 code implementation6 Nov 2021 Ibrahim Salihu Yusuf, Kale-ab Tessera, Thomas Tumiel, Zohra Slim, Amine Kerkeni, Sella Nevo, Arnu Pretorius

In this paper, we compare this random sampling approach to more advanced pseudo-absence generation methods, such as environmental profiling and optimal background extent limitation, specifically for predicting desert locust breeding grounds in Africa.

regression

Physics-Aware Downsampling with Deep Learning for Scalable Flood Modeling

1 code implementation NeurIPS 2021 Niv Giladi, Zvika Ben-Haim, Sella Nevo, Yossi Matias, Daniel Soudry

Background: Floods are the most common natural disaster in the world, affecting the lives of hundreds of millions.

ML-based Flood Forecasting: Advances in Scale, Accuracy and Reach

no code implementations29 Nov 2020 Sella Nevo, Gal Elidan, Avinatan Hassidim, Guy Shalev, Oren Gilon, Grey Nearing, Yossi Matias

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.

HydroNets: Leveraging River Structure for Hydrologic Modeling

no code implementations1 Jul 2020 Zach Moshe, Asher Metzger, Gal Elidan, Frederik Kratzert, Sella Nevo, Ran El-Yaniv

In this work we present a novel family of hydrologic models, called HydroNets, which leverages river network structure.

Management

Accurate Hydrologic Modeling Using Less Information

no code implementations21 Nov 2019 Guy Shalev, Ran El-Yaniv, Daniel Klotz, Frederik Kratzert, Asher Metzger, Sella Nevo

Joint models are a common and important tool in the intersection of machine learning and the physical sciences, particularly in contexts where real-world measurements are scarce.

Spectral Algorithm for Low-rank Multitask Regression

no code implementations27 Oct 2019 Yotam Gigi, Ami Wiesel, Sella Nevo, Gal Elidan, Avinatan Hassidim, Yossi Matias

In this scenario sharing a low-rank component between the tasks translates to a shared spectral reflection of the water, which is a true underlying physical model.

Image Classification regression

Inundation Modeling in Data Scarce Regions

no code implementations11 Oct 2019 Zvika Ben-Haim, Vladimir Anisimov, Aaron Yonas, Varun Gulshan, Yusef Shafi, Stephan Hoyer, Sella Nevo

Flood forecasts are crucial for effective individual and governmental protective action.

ML for Flood Forecasting at Scale

no code implementations28 Jan 2019 Sella Nevo, Vova Anisimov, Gal Elidan, Ran El-Yaniv, Pete Giencke, Yotam Gigi, Avinatan Hassidim, Zach Moshe, Mor Schlesinger, Guy Shalev, Ajai Tirumali, Ami Wiesel, Oleg Zlydenko, Yossi Matias

We propose to build on these strengths and develop ML systems for timely and accurate riverine flood prediction.

Towards Global Remote Discharge Estimation: Using the Few to Estimate The Many

no code implementations3 Jan 2019 Yotam Gigi, Gal Elidan, Avinatan Hassidim, Yossi Matias, Zach Moshe, Sella Nevo, Guy Shalev, Ami Wiesel

We demonstrate the efficacy of our approach for the problem of discharge estimation using simulations.

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