The DOI matches its Crossref record; 229 of the 229 references it cites were found in a registry or an index.
Deep learning in hydrology and water resources disciplines: concepts, methods, applications, and research directions
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Citations
Cites
1 retracted
Kaur, S., Gupta, S., Singh, S., Koundal, D., & Zaguia, A. (2022) · Soft Computing · doi:10.1007/s00500-022-06805-6 · Cited by 39
RetractedBreiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
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Gradient-based learning applied to document recognition
Lecun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998) · Proceedings of the IEEE · doi:10.1109/5.726791 · Cited by 58,805
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482
Going deeper with convolutions
Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., & Rabinovich, A. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298594 · Cited by 48,562
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Learning representations by back-propagating errors
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986) · Nature · doi:10.1038/323533a0 · Cited by 31,892
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., et al. (2020) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.3803 · Cited by 31,882
Greedy function approximation: A gradient boosting machine
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Cited by
Huynh, N. N. T., Garambois, P.-A., Renard, B., Colleoni, F., Monnier, J., & Roux, H. (2025) · Hydrology and Earth System Sciences · doi:10.5194/hess-29-3589-2025 · Cited by 38
Metadata
- Authors
- Tripathy, K. P., & Mishra, A. K.
- Venue
- Journal of Hydrology
- Publisher
- Elsevier BV
- Published
- 2024-01
- Volume
- 628
- Pages
- 130458
- ISSN
- 0022-1694 (ISSN-L)
- OpenAlex
- W4388686886
- Cited by
- 336
- References
- 229
- FWCI
- 27.99
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: Deep learning in hydrology and water resources disciplines: concepts, methods, applications, and research directions. https://app.cochat.ai/papers/10.1016/j.jhydrol.2023.130458
- The paper
- Tripathy, K. P., & Mishra, A. K. (2024). Deep learning in hydrology and water resources disciplines: concepts, methods, applications, and research directions. Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2023.130458
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
