Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Shalev, Guy"'
Autor:
Nearing, Grey, Cohen, Deborah, Dube, Vusumuzi, Gauch, Martin, Gilon, Oren, Harrigan, Shaun, Hassidim, Avinatan, Klotz, Daniel, Kratzert, Frederik, Metzger, Asher, Nevo, Sella, Pappenberger, Florian, Prudhomme, Christel, Shalev, Guy, Shenzis, Shlomo, Tekalign, Tadele, Weitzner, Dana, Matias, Yoss
Floods are one of the most common natural disasters, with a disproportionate impact in developing countries that often lack dense streamflow gauge networks. Accurate and timely warnings are critical for mitigating flood risks, but hydrological simula
Externí odkaz:
http://arxiv.org/abs/2307.16104
Autor:
Nevo, Sella, Morin, Efrat, Rosenthal, Adi Gerzi, Metzger, Asher, Barshai, Chen, Weitzner, Dana, Voloshin, Dafi, Kratzert, Frederik, Elidan, Gal, Dror, Gideon, Begelman, Gregory, Nearing, Grey, Shalev, Guy, Noga, Hila, Shavitt, Ira, Yuklea, Liora, Royz, Moriah, Giladi, Niv, Levi, Nofar Peled, Reich, Ofir, Gilon, Oren, Maor, Ronnie, Timnat, Shahar, Shechter, Tal, Anisimov, Vladimir, Gigi, Yotam, Levin, Yuval, Moshe, Zach, Ben-Haim, Zvika, Hassidim, Avinatan, Matias, Yossi
The operational flood forecasting system by Google was developed to provide accurate real-time flood warnings to agencies and the public, with a focus on riverine floods in large, gauged rivers. It became operational in 2018 and has since expanded ge
Externí odkaz:
http://arxiv.org/abs/2111.02780
Autor:
Nevo, Sella, Elidan, Gal, Hassidim, Avinatan, Shalev, Guy, Gilon, Oren, Nearing, Grey, Matias, Yossi
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 world's vulnerable population does not have access to reliable and actiona
Externí odkaz:
http://arxiv.org/abs/2012.00671
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. Recent developments in rainfall-runoff modeling, one of the prime chall
Externí odkaz:
http://arxiv.org/abs/1911.09427
Autor:
Kratzert, Frederik, Klotz, Daniel, Shalev, Guy, Klambauer, Günter, Hochreiter, Sepp, Nearing, Grey
Regional rainfall-runoff modeling is an old but still mostly out-standing problem in Hydrological Sciences. The problem currently is that traditional hydrological models degrade significantly in performance when calibrated for multiple basins togethe
Externí odkaz:
http://arxiv.org/abs/1907.08456
Autor:
Nevo, Sella, Anisimov, Vova, Elidan, Gal, El-Yaniv, Ran, Giencke, Pete, Gigi, Yotam, Hassidim, Avinatan, Moshe, Zach, Schlesinger, Mor, Shalev, Guy, Tirumali, Ajai, Wiesel, Ami, Zlydenko, Oleg, Matias, Yossi
Effective riverine flood forecasting at scale is hindered by a multitude of factors, most notably the need to rely on human calibration in current methodology, the limited amount of data for a specific location, and the computational difficulty of bu
Externí odkaz:
http://arxiv.org/abs/1901.09583
Autor:
Gigi, Yotam, Elidan, Gal, Hassidim, Avinatan, Matias, Yossi, Moshe, Zach, Nevo, Sella, Shalev, Guy, Wiesel, Ami
Learning hydrologic models for accurate riverine flood prediction at scale is a challenge of great importance. One of the key difficulties is the need to rely on in-situ river discharge measurements, which can be quite scarce and unreliable, particul
Externí odkaz:
http://arxiv.org/abs/1901.00786
Autor:
Shalev, Guy
The Fourier Entropy-Influence (FEI) Conjecture of Friedgut and Kalai states that ${\bf H}[f] \leq C \cdot {\bf I}[f]$ holds for every Boolean function $f$, where ${\bf H}[f]$ denotes the spectral entropy of $f$, ${\bf I}[f]$ is its total influence, a
Externí odkaz:
http://arxiv.org/abs/1806.03646
Autor:
Nearing, Grey, Cohen, Deborah, Dube, Vusumuzi, Gauch, Martin, Gilon, Oren, Harrigan, Shaun, Hassidim, Avinatan, Klotz, Daniel, Kratzert, Frederik, Metzger, Asher, Nevo, Sella, Pappenberger, Florian, Prudhomme, Christel, Shalev, Guy, Shenzis, Shlomo, Tekalign, Tadele Yednkachw, Weitzner, Dana, Matias, Yossi
Publikováno v:
Nature; Mar2024, Vol. 627 Issue 8004, p559-563, 5p
Akademický článek
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