42 citations as recorded by crossref.

1. Neural Synthetic Profiles from Remote Sensing and Observations (NeSPReSO) — Reconstructing temperature and salinity fields in the Gulf of Mexico J. Miranda et al.
2. Reconstructing ocean subsurface salinity at high resolution using a machine learning approach T. Tian et al.
3. EOF-UViT Model: A New Deep Learning Model to Reconstruct the Three-Dimensional Salinity Based on Multi-Source Remote Sensing Data X. Han et al.
4. Deep learning-driven 3D marine nitrate estimation: uncertainty mitigation through underwater signal exploitation and label augmentation X. Yu et al.
5. An Updated Estimate of the Indonesian Throughflow Geostrophic Transport: Interannual Variability and Salinity Effect Y. Guo et al.
6. A comparative assessment of different machine learning algorithms for estimating near realistic salinity in the North Indian Ocean A. Paul et al.
7. Reconstructing three-dimensional density from surface data in the North Atlantic Sea through the PIO-Net model Y. Chen et al.
8. Daily Subsurface Salinity Reconstruction From Multisource Satellite Observations Using Wavelet-Enhanced 3-D Mamba Z. Liang et al.
9. CoastalBench-downscaling: a machine learning benchmark for reconstructing high-resolution three-dimensional coastal fields from surface data B. Yuan et al.
10. Assessment of wetland ecosystem health in Rarh Region, India through P-S-R (pressure-state-response) model R. Khatun & S. Das
11. Decreases in South Pacific and South Atlantic sea-air CO2 fluxes caused by extreme precipitation Z. Li et al.
12. Reconstructing high-resolution subsurface temperature of the global ocean using deep forest with combined remote sensing and in situ observations H. Su et al.
13. Super-resolution reconstruction of subsurface temperature field in South China Sea using satellite observations H. Wu et al.
14. Estimation of subsurface salinity and analysis of Changjiang diluted water volume in the East China Sea S. Kim et al.
15. A deep learning approach to estimate ocean salinity with data sampled with expendable bathythermographs E. Campos et al.
16. On the global reconstruction of ocean interior variables: a feasibility data-driven study with simulated surface and water column observations A. Garcia-Espriu et al.
17. Enhancing Subsurface Thermal Structures Reconstruction via a Dual-Branch Framework Integrating Surface Remote Sensing and Model-Predicted Upper-Layer Fields C. Zhou et al.
18. Learn from Simulations, Adapt to Observations: Super-Resolution of Isoprene Emissions via Unpaired Domain Adaptation A. Giganti et al.
19. Reconstruction of the underwater sound speed field of mesoscale eddies in typical sea areas based on the physically-constrained deep learning model Y. Liu et al.
20. A continual-learning-based multilayer perceptron for improved reconstruction of three-dimensional nitrate concentrations X. Yu et al.
21. Knowledge-Informed Deep Learning Model for Subsurface Thermohaline Reconstruction From Satellite Observations A. Wang et al.
22. OceanVP: A HYCOM based benchmark dataset and a relational spatiotemporal predictive network for oceanic variable prediction Z. Shi et al.
23. Bias Correction of SMAP L2 Sea Surface Salinity Based on Physics-Informed Neural Network M. Wu et al.
24. A Method for Predicting High-Resolution 3D Variations in Temperature and Salinity Fields Using Multi-Source Ocean Data X. Cao et al.
25. A New Region Ocean Sound Velocity Field Model Considering Variation Mechanisms of Temperature and Salt X. Zhao et al.
26. Application of swarm-based deep neural networks and ensemble models for reconstruction of specific conductance data A. Mahdavi-Meymand et al.
27. Attention-enhanced deep learning model for reconstruction and downscaling of thermocline depth in the tropical Indian Ocean Z. Feng et al.
28. Strengthening ITF and weakening AMOC: time series evidence of trends and causal pathways to Agulhas variability S. Herho et al.
29. Enhancing Ocean Temperature and Salinity Reconstruction with Deep Learning: The Role of Surface Waves X. Yu et al.
30. Leveraging Land Cover Priors for Isoprene Emission Super-Resolution C. Ummerle et al.
31. 3DV-Unet: Eddy-Resolving Reconstruction of Three-Dimensional Upper-Ocean Physical Fields from Satellite Observations Q. Zhu et al.
32. Skillful subseasonal Indian Ocean marine heatwave forecasts using a neural network L. Howard et al.
33. STMSNet: A Novel Spatiotemporal Deep Learning Model for Ocean Subsurface Temperature Reconstruction H. Chen et al.
34. Uncertainty Quantification of Satellite-Based Essential Climate Variables Derived from Deep Learning J. Gou et al.
35. Reconstruction of Three-Dimensional Temperature and Salinity in the Equatorial Ocean with Deep-Learning X. Yu et al.
36. Advancing ocean subsurface thermal structure estimation in the Pacific Ocean: A multi-model ensemble machine learning approach J. Qi et al.
37. Forecasting Vertical Profiles of Ocean Currents from Surface Characteristics: A Multivariate Multi-Head Convolutional Neural Network–Long Short-Term Memory Approach S. Kar et al.
38. Comparison of Machine Learning Inversion Methods for Salinity in the Central Indian Ocean Based on SMOS Satellite Data Z. Gong et al.
39. Reconstructing 3D ocean subsurface salinity (OSS) from T–S mapping via a data-driven deep learning model J. Zhang et al.
40. Cross-scale 3-D thermohaline modeling via dual-residual swin transformer with multisource ocean observations A. Wang et al.
41. Machine learning reconstruction of multiyear missing nutrient data along the 137°E section, northwestern Pacific X. Song et al.
42. A prior-knowledge-integrated downscaling approach for subsurface thermal structure reconstruction in the tropical Indian Ocean Z. Feng et al.