OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
NeuralHydrology — A Python library for Deep Learning research in hydrology
Frederik Kratzert, Martin Gauch, Grey Nearing, et al.
The Journal of Open Source Software (2022) Vol. 7, Iss. 71, pp. 4050-4050
Open Access | Times Cited: 136
Frederik Kratzert, Martin Gauch, Grey Nearing, et al.
The Journal of Open Source Software (2022) Vol. 7, Iss. 71, pp. 4050-4050
Open Access | Times Cited: 136
Showing 26-50 of 136 citing articles:
The Great Lakes Runoff Intercomparison Project Phase 4: The Great Lakes (GRIP-GL)
Juliane Mai, Hongren Shen, Bryan A. Tolson, et al.
(2022)
Open Access | Times Cited: 19
Juliane Mai, Hongren Shen, Bryan A. Tolson, et al.
(2022)
Open Access | Times Cited: 19
Technical Note: The Divide and Measure Nonconformity
Daniel Klotz, Martin Gauch, Frederik Kratzert, et al.
(2024)
Open Access | Times Cited: 3
Daniel Klotz, Martin Gauch, Frederik Kratzert, et al.
(2024)
Open Access | Times Cited: 3
Hyperparameter optimization of regional hydrological LSTMs by random search: A case study from Basque Country, Spain
Fateme Hosseini, Cristina Prieto, César Álvarez
Journal of Hydrology (2024), pp. 132003-132003
Open Access | Times Cited: 3
Fateme Hosseini, Cristina Prieto, César Álvarez
Journal of Hydrology (2024), pp. 132003-132003
Open Access | Times Cited: 3
Opportunities and limitations of the ChatGPT Advanced Data Analysis plugin for hydrological analyses
Dylan J. Irvine, Landon J. S. Halloran, Philip Brunner
Hydrological Processes (2023) Vol. 37, Iss. 10
Open Access | Times Cited: 9
Dylan J. Irvine, Landon J. S. Halloran, Philip Brunner
Hydrological Processes (2023) Vol. 37, Iss. 10
Open Access | Times Cited: 9
Streamflow Predictions in Ungauged Basins Using Recurrent Neural Network and Decision Tree-Based Algorithm: Application to the Southern Region of the Korean Peninsula
Jeongeun Won, Jiyu Seo, Jeonghoon Lee, et al.
Water (2023) Vol. 15, Iss. 13, pp. 2485-2485
Open Access | Times Cited: 8
Jeongeun Won, Jiyu Seo, Jeonghoon Lee, et al.
Water (2023) Vol. 15, Iss. 13, pp. 2485-2485
Open Access | Times Cited: 8
Michael Vlah, Spencer Rhea, Emily S. Bernhardt, et al.
Limnology and Oceanography Letters (2023) Vol. 8, Iss. 3, pp. 419-452
Open Access | Times Cited: 7
Leveraging gauge networks and strategic discharge measurements to aid the development of continuous streamflow records
Michael Vlah, Matthew Ross, Spencer Rhea, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 3, pp. 545-573
Open Access | Times Cited: 2
Michael Vlah, Matthew Ross, Spencer Rhea, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 3, pp. 545-573
Open Access | Times Cited: 2
Technical Note: The divide and measure nonconformity – how metrics can mislead when we evaluate on different data partitions
Daniel Klotz, Martin Gauch, Frederik Kratzert, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 15, pp. 3665-3673
Open Access | Times Cited: 2
Daniel Klotz, Martin Gauch, Frederik Kratzert, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 15, pp. 3665-3673
Open Access | Times Cited: 2
Enhancing Streamflow Prediction in Ungauged Basins Using a Nonlinear Knowledge‐Based Framework and Deep Learning
Parnian Ghaneei, Ehsan Foroumandi, Hamid Moradkhani
Water Resources Research (2024) Vol. 60, Iss. 11
Open Access | Times Cited: 2
Parnian Ghaneei, Ehsan Foroumandi, Hamid Moradkhani
Water Resources Research (2024) Vol. 60, Iss. 11
Open Access | Times Cited: 2
MacroSheds: a synthesis of long-term biogeochemical, hydroclimatic, and geospatial data from small watershed ecosystem studies
Michael Vlah, Spencer Rhea, Emily S. Bernhardt, et al.
EarthArXiv (California Digital Library) (2022)
Open Access | Times Cited: 11
Michael Vlah, Spencer Rhea, Emily S. Bernhardt, et al.
EarthArXiv (California Digital Library) (2022)
Open Access | Times Cited: 11
Never train an LSTM on a single basin
Frederik Kratzert, Martin Gauch, Daniel Klotz, et al.
EarthArXiv (California Digital Library) (2023)
Open Access | Times Cited: 5
Frederik Kratzert, Martin Gauch, Daniel Klotz, et al.
EarthArXiv (California Digital Library) (2023)
Open Access | Times Cited: 5
A National Scale Hybrid Model for Enhanced Streamflow Estimation – Consolidating a Physically Based Hydrological Model with Long Short-term Memory Networks
Jun Liu, Julian Koch, Simon Stisen, et al.
(2023)
Open Access | Times Cited: 4
Jun Liu, Julian Koch, Simon Stisen, et al.
(2023)
Open Access | Times Cited: 4
Analyzing the generalization capabilities of hybrid hydrological models for extrapolation to extreme events
Eduardo Acuña Espinoza, Ralf Loritz, Frederik Kratzert, et al.
(2024)
Open Access | Times Cited: 1
Eduardo Acuña Espinoza, Ralf Loritz, Frederik Kratzert, et al.
(2024)
Open Access | Times Cited: 1
Ensemble learning of catchment-wise optimized LSTMs enhances regional rainfall-runoff modelling − case Study: Basque Country, Spain
Farzad Hosseini Hossein Abadi, Cristina Prieto, César Álvarez
Journal of Hydrology (2024), pp. 132269-132269
Open Access | Times Cited: 1
Farzad Hosseini Hossein Abadi, Cristina Prieto, César Álvarez
Journal of Hydrology (2024), pp. 132269-132269
Open Access | Times Cited: 1
Synergizing Intuitive Physics and Big Data in Deep Learning: Can We Obtain Process Insights While Maintaining State‐Of‐The‐Art Hydrological Prediction Capability?
Leilei He, Liangsheng Shi, Wenxiang Song, et al.
Water Resources Research (2024) Vol. 60, Iss. 12
Open Access | Times Cited: 1
Leilei He, Liangsheng Shi, Wenxiang Song, et al.
Water Resources Research (2024) Vol. 60, Iss. 12
Open Access | Times Cited: 1
Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations
Yuhang Zhang, Aizhong Ye, Bita Analui, et al.
Hydrology and earth system sciences (2023) Vol. 27, Iss. 24, pp. 4529-4550
Open Access | Times Cited: 4
Yuhang Zhang, Aizhong Ye, Bita Analui, et al.
Hydrology and earth system sciences (2023) Vol. 27, Iss. 24, pp. 4529-4550
Open Access | Times Cited: 4
Continuous streamflow prediction in ungauged basins: Long Short-Term Memory Neural Networks clearly outperform hydrological models
Richard Arsenault, Jean‐Luc Martel, Frédéric Brunet, et al.
(2022)
Open Access | Times Cited: 7
Richard Arsenault, Jean‐Luc Martel, Frédéric Brunet, et al.
(2022)
Open Access | Times Cited: 7
Towards Interpretable LSTM-based Modelling of Hydrological Systems
Luis De La Fuente, Mohammad Reza Ehsani, Hoshin V. Gupta, et al.
(2023)
Open Access | Times Cited: 3
Luis De La Fuente, Mohammad Reza Ehsani, Hoshin V. Gupta, et al.
(2023)
Open Access | Times Cited: 3
Deep learning for monthly rainfall-runoff modelling: a comparison with classical rainfall-runoff modelling across Australia
Stephanie Clark, Julien Lerat, Jean‐Michel Perraud, et al.
(2023)
Open Access | Times Cited: 2
Stephanie Clark, Julien Lerat, Jean‐Michel Perraud, et al.
(2023)
Open Access | Times Cited: 2
Impact of Training Dataset Size and Its Hydrometeorological Typology on LSTM Performance for Rainfall-Runoff Modeling: A Case Study of the Severn River
Nadia Skifa, Fadil Boodoo, Carole Delenne, et al.
Springer water (2024), pp. 107-128
Open Access
Nadia Skifa, Fadil Boodoo, Carole Delenne, et al.
Springer water (2024), pp. 107-128
Open Access
