Benchmarking a Catchment-Aware Long Short-Term Memory Network (LSTM) for Large-Scale Hydrological Modeling. - Frederik Kratzert; Daniel Klotz; Guy Shalev; Günter Klambauer; Sepp Hochreiter; Grey Nearing (CoRR, 2019)

Using LSTMs for climate change assessment studies on droughts and floods. - Frederik Kratzert; Daniel Klotz; Johannes Brandstetter; Pieter-Jan Hoedt; Grey Nearing; Sepp Hochreiter (CoRR, 2019)

Combining Parametric Land Surface Models with Machine Learning. - Craig Pelissier; Jonathan Frame; Grey Nearing (IGARSS, 2020)

Rainfall-Runoff Prediction at Multiple Timescales with a Single Long Short-Term Memory Network. - Martin Gauch; Frederik Kratzert; Daniel Klotz; Grey Nearing; Jimmy Lin; Sepp Hochreiter (CoRR, 2020)

ML-based Flood Forecasting: Advances in Scale, Accuracy and Reach. - Sella Nevo; Gal Elidan; Avinatan Hassidim; Guy Shalev; Oren Gilon; Grey Nearing; Yossi Matias (CoRR, 2020)

Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling. - Daniel Klotz; Frederik Kratzert; Martin Gauch; Alden Keefe Sampson; Günter Klambauer; Sepp Hochreiter; Grey Nearing (CoRR, 2020)

MC-LSTM: Mass-Conserving LSTM. - Pieter-Jan Hoedt; Frederik Kratzert; Daniel Klotz; Christina Halmich; Markus Holzleitner; Grey Nearing; Sepp Hochreiter; Günter Klambauer (ICML, 2021)

Flood forecasting with machine learning models in an operational framework. - Sella Nevo; Efrat Morin; Adi Gerzi Rosenthal; Asher Metzger; Chen Barshai; Dana Weitzner; Dafi Voloshin; Frederik Kratzert; Gal Elidan; Gideon Dror; Gregory Begelman; Grey Nearing; et al. (CoRR, 2021)

Ten simple rules to cultivate transdisciplinary collaboration in data science. - Faryad Sahneh; Meghan A. Balk; Marina Kisley; Chi-Kwan Chan; Mercury Fox; Brian Nord; Eric Lyons 002; Tyson Lee Swetnam; Daniela Huppenkothen; Will Sutherland; Ramona L. Walls; Daven P. Quinn; et al. (PLoS Comput. Biol., 2021)

A Machine Learning Data Fusion Model for Soil Moisture Retrieval. - Vishal Batchu; Grey Nearing; Varun Gulshan (CoRR, 2022)

NeuralHydrology - A Python library for Deep Learning research in hydrology. - Frederik Kratzert; Martin Gauch; Grey Nearing; Daniel Klotz (J. Open Source Softw., 2022)

AI Increases Global Access to Reliable Flood Forecasts. - Grey Nearing; Deborah Cohen; Vusumuzi Dube; Martin Gauch; Oren Gilon; Shaun Harrigan; Avinatan Hassidim; Frederik Kratzert; Asher Metzger; Sella Nevo; Florian Pappenberger; Christel Prudhomme; et al. (CoRR, 2023)

Fine Flood Forecasts: Incorporating local data into global models through fine-tuning. - Emil Ryd; Grey Nearing (CoRR, 2025)

A Physically Driven Long Short Term Memory Model for Estimating Snow Water Equivalent over the Continental United States. - Arun M. Saranathan; Mahmoud Saeedimoghaddam; Brandon Smith; Deepthi Raghunandan; Grey Nearing; Craig Pelissier (CoRR, 2025)