Open Access Helper

OpenAlex Citation Counts

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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:

A differentiable, physics-informed ecosystem modeling and learning framework for large-scale inverse problems: demonstration with photosynthesis simulations
Doaa Aboelyazeed, Chonggang Xu, Forrest M. Hoffman, et al.
Biogeosciences (2023) Vol. 20, Iss. 13, pp. 2671-2692
Open Access | Times Cited: 23

Showing 23 citing articles:

Improving River Routing Using a Differentiable Muskingum‐Cunge Model and Physics‐Informed Machine Learning
Tadd Bindas, Wen‐Ping Tsai, Jiangtao Liu, et al.
Water Resources Research (2024) Vol. 60, Iss. 1
Open Access | Times Cited: 24
Probing the limit of hydrologic predictability with the Transformer network
Jiangtao Liu, Yuchen Bian, Kathryn Lawson, et al.
Journal of Hydrology (2024) Vol. 637, pp. 131389-131389
Open Access | Times Cited: 12
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Yalan Song, Wouter Knoben, Martyn Clark, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 13, pp. 3051-3077
Open Access | Times Cited: 6
JAX‐CanVeg: A Differentiable Land Surface Model
Peishi Jiang, Patrick Kidger, Toshiyuki Bandai, et al.
Water Resources Research (2025) Vol. 61, Iss. 3
Open Access
High‐Resolution National‐Scale Water Modeling Is Enhanced by Multiscale Differentiable Physics‐Informed Machine Learning
Yalan Song, Tadd Bindas, Chaopeng Shen, et al.
Water Resources Research (2025) Vol. 61, Iss. 4
Open Access
Plant science in the age of simulation intelligence
Michiel Stock, Olivier Pieters, Tom De Swaef, et al.
Frontiers in Plant Science (2024) Vol. 14
Open Access | Times Cited: 4
Deep learning insights into suspended sediment concentrations across the conterminous United States: Strengths and limitations
Yalan Song, Piyaphat Chaemchuen, Farshid Rahmani, et al.
Journal of Hydrology (2024) Vol. 639, pp. 131573-131573
Closed Access | Times Cited: 4
Deep dive into hydrologic simulations at global scale: harnessing the power of deep learning and physics-informed differentiable models (δHBV-globe1.0-hydroDL)
Dapeng Feng, Hylke E. Beck, Jens de Bruijn, et al.
Geoscientific model development (2024) Vol. 17, Iss. 18, pp. 7181-7198
Open Access | Times Cited: 4
A Surrogate Model for Shallow Water Equations Solvers with Deep Learning
Yalan Song, Chaopeng Shen, Xiaofeng Liu
Journal of Hydraulic Engineering (2023) Vol. 149, Iss. 11
Open Access | Times Cited: 9
Identifying Structural Priors in a Hybrid Differentiable Model for Stream Water Temperature Modeling
Farshid Rahmani, Alison P. Appling, Dapeng Feng, et al.
Water Resources Research (2023) Vol. 59, Iss. 12
Open Access | Times Cited: 9
Bathymetry Inversion Using a Deep‐Learning‐Based Surrogate for Shallow Water Equations Solvers
Xiaofeng Liu, Yalan Song, Chaopeng Shen
Water Resources Research (2024) Vol. 60, Iss. 3
Open Access | Times Cited: 3
Dung beetle optimization with deep learning approach for solving inverse problems in predicting financial futures
Hind Alnafisah, Hiyam Abdulrahim, Abaker A. Hassaballa, et al.
Alexandria Engineering Journal (2024) Vol. 109, pp. 71-82
Open Access | Times Cited: 3
The intricacies of vegetation responses to changing moisture conditions
Julia K. Green
New Phytologist (2024) Vol. 244, Iss. 6, pp. 2156-2162
Open Access | Times Cited: 2
Exploring Optimal Complexity for Water Stress Representation in Terrestrial Carbon Models: A Hybrid‐Machine Learning Model Approach
Jianing Fang, Pierre Gentine
Journal of Advances in Modeling Earth Systems (2024) Vol. 16, Iss. 12
Open Access | Times Cited: 1
Global Daily Discharge Estimation Based on Grid-Scale Long Short-Term Memory (LSTM) Model and River Routing
Yuan Yang, Dapeng Feng, Hylke E. Beck, et al.
Authorea (Authorea) (2023)
Open Access | Times Cited: 4
Reply on RC2
Chaopeng Shen
(2024)
Open Access
Reply on RC1
Chaopeng Shen
(2024)
Open Access
Reply on RC2
Chaopeng Shen
(2024)
Open Access
Reply on RC3
Chaopeng Shen
(2024)
Open Access
Exploring Optimal Complexity for Water Stress Representation in Terrestrial Carbon Models: A Hybrid-Machine Learning Model Approach
Jianing Fang, Pierre Gentine
Authorea (Authorea) (2024)
Open Access
Simulating the land carbon sink: Progresses and challenges of terrestrial ecosystem models
Wenping Yuan, Jiangzhou Xia, Chaoqing Song, et al.
Agricultural and Forest Meteorology (2024) Vol. 358, pp. 110264-110264
Open Access
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Yalan Song, Wouter Knoben, Martyn Clark, et al.
(2023)
Open Access | Times Cited: 1
Comment on hess-2023-258
Ilhan Özgen‐Xian
(2023)
Open Access
Comment on hess-2023-258
Uwe Ehret
(2023)
Open Access
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