Rainfall–runoff prediction at multiple timescales with a single Long Short-Term Memory network by M. Gauch, M. Gauch, F. Kratzert, D. Klotz, G. Nearing, G. Nearing, J. Lin, S. Hochreiter

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Uncertainty estimation with deep learning for rainfall–runoff modeling by D. Klotz, F. Kratzert, M. Gauch, A. Keefe Sampson, J. Brandstetter, G. Klambauer, S. Hochreiter, G. Nearing

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Technical note: Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks by G. S. Nearing, D. Klotz, J. M. Frame, M. Gauch, O. Gilon, F. Kratzert, A. K. Sampson, G. Shalev, S. Nevo

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Deep learning rainfall–runoff predictions of extreme events by J. M. Frame, J. M. Frame, F. Kratzert, D. Klotz, M. Gauch, G. Shelev, O. Gilon, L. M. Qualls, H. V. Gupta, G. S. Nearing

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Hydrological concept formation inside long short-term memory (LSTM) networks by T. Lees, T. Lees, S. Reece, F. Kratzert, D. Klotz, M. Gauch, J. De Bruijn, J. De Bruijn, R. Kumar Sahu, P. Greve, L. Slater, S. J. Dadson, S. J. Dadson

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The Great Lakes Runoff Intercomparison Project Phase 4: the Great Lakes (GRIP-GL) by J. Mai, H. Shen, B. A. Tolson, É. Gaborit, R. Arsenault, J. R. Craig, V. Fortin, L. M. Fry, M. Gauch, D. Klotz, F. Kratzert, F. Kratzert, N. O'Brien, D. G. Princz, S. Rasiya Koya, T. Roy, F. Seglenieks, N. K. Shrestha, A. G. T. Temgoua, V. Vionnet, J. W. Waddell

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