G. Shalev

发表

Technical Note: Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks

Sella Nevo, G. Nearing, D. Klotz, 2021, Hydrology and Earth System Sciences.

Flood forecasting with machine learning models in an operational framework pdf

Yossi Matias, Avinatan Hassidim, Gal Elidan, 2021, Hydrology and Earth System Sciences.

Modeling COVID-19 on a network: super-spreaders, testing and containment

O. Reich, T. Kalvari, G. Shalev, 2020, medRxiv.

Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets

S. Hochreiter, G. Klambauer, G. Nearing, 2019, Hydrology and Earth System Sciences.

Benchmarking a Catchment-Aware Long Short-Term Memory Network (LSTM) for Large-Scale Hydrological Modeling pdf

Sepp Hochreiter, Frederik Kratzert, Daniel Klotz, 2019, ArXiv.

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

Ami Wiesel, Yossi Matias, Avinatan Hassidim, 2019, ArXiv.

Hybrid forecasting: blending climate predictions with AI models

M. Boucher, R. Wilby, M. Zappa, 2023, Hydrology and Earth System Sciences.

Hybrid forecasting: using statistics and machine learning to integrate predictions from dynamical models

M. Boucher, R. Wilby, M. Zappa, 2022 .

Caravan - A global community dataset for large-sample hydrology

Sella Nevo, Avinatan Hassidim, N. Addor, 2023, Scientific Data.

AI Increases Global Access to Reliable Flood Forecasts

Sella Nevo, Avinatan Hassidim, F. Pappenberger, 2023, arXiv.org.