W D Watkins

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All published works

Action	Title	Year	Authors
+ PDF Chat	Physics-Guided Neural Networks (PGNN): An Application in Lake Temperature Modeling	2022	Arka Daw Anuj Karpatne W D Watkins Jordan S. Read Vipin Kumar
+ PDF Chat	Near-term forecasts of stream temperature using process-guided deep learning and data assimilation	2021	Jacob A. Zwart Samantha K. Oliver W D Watkins Jeffrey M. Sadler Alison Appling Hayley Corson-Dosch Xiaowei Jia Vipin Kumar Jordan S. Read

Common Coauthors

Coauthor	Papers Together
Jordan S. Read	2
Vipin Kumar	2
Samantha K. Oliver	1
Jeffrey M. Sadler	1
Xiaowei Jia	1
Arka Daw	1
Anuj Karpatne	1
Hayley Corson-Dosch	1
Alison Appling	1
Jacob A. Zwart	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Neural network closures for nonlinear model order reduction	2018	Omer San Romit Maulik	1
+	Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data	2017	Anuj Karpatne Gowtham Atluri James H. Faghmous Michael Steinbach Arindam Banerjee Auroop R. Ganguly Shashi Shekhar Nagiza Samatova Vipin Kumar	1
+ PDF Chat	Data-assisted reduced-order modeling of extreme events in complex dynamical systems	2018	Zhong Wan Pantelis R. Vlachas Petros Koumoutsakos Themistoklis P. Sapsis	1
+ PDF Chat	Rainfall–runoff modelling using Long Short-Term Memory (LSTM) networks	2018	Frederik Kratzert Daniel Klotz Claire Brenner Karsten Schulz Mathew Herrnegger	1
+ PDF Chat	Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets	2019	Frederik Kratzert Daniel Klotz Guy Shalev Günter Klambauer Sepp Hochreiter Grey Nearing	1
+ PDF Chat	Distributed long-term hourly streamflow predictions using deep learning – A case study for State of Iowa	2020	Zhongrun Xiang İbrahim Demir	1
+	Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: A case study with the Lorenz 96 model	2020	Julien Brajard Alberto Carrassi Marc Bocquet Laurent Bertino	1
+ PDF Chat	A Transdisciplinary Review of Deep Learning Research and Its Relevance for Water Resources Scientists	2018	Chaopeng Shen	1
+	Uncertainty Estimation with Deep Learning for Rainfall–Runoff Modelling	2021	Daniel Klotz Frederik Kratzert Martin Gauch Alden Keefe Sampson J. Brandstetter Günter Klambauer Sepp Hochreiter Grey Nearing	1
+	Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning	2015	Yarin Gal Zoubin Ghahramani	1
+	ADADELTA: An Adaptive Learning Rate Method	2012	Matthew D. Zeiler	1