Latest Research in Machine Learning

Top Research Topics in Machine Learning

• Machine Learning — 9 papers
• Meteorological Phenomena and Simulations — 7 papers
• Atmospheric aerosols and clouds — 4 papers
• Atmospheric and Oceanic Physics — 4 papers
• Precipitation Measurement and Analysis — 3 papers
• Tropical and Extratropical Cyclones Research — 1 papers
• Distributed, Parallel, and Cluster Computing — 1 papers
• Landslides and related hazards — 1 papers
• Wind Energy Research and Development — 1 papers
• Advanced SAR Imaging Techniques — 1 papers

Highest-Cited Papers

1. A barycenter-based approach for the multi-model ensembling of subseasonal forecasts (1 citations)
2. Tropical Cyclone Precipitation Nowcasting Based on Flow Matching Model With Numerical Wind Field Constraints
3. IRENE: A Convolutional GRU Ensemble Model for Radar Precipitation Nowcasting over Italy
4. Cross-Validation of Collocated ICESat-2 and CALIPSO Cloud-Aerosol Discrimination
5. Real-World Deployment and Performance Characterisation of Fog-Based Deep Learning for Cold-Chain Temperature Prediction over LoRaWAN
6. Multi-satellite data fusion for upper tropospheric humidity using a novel deep learning architecture
7. Seismic Observations from Two Long-Track EF4 Tornadoes in the Central United States
8. Spatiotemporal autocorrelation of landslides in neighborhoods of Recife, Brazil (2015–2024) based on the Moran and Lisa index
9. KiloDA: Reconstructing kilometer-scale near-surface wind states from sparse station observations
10. Improving precipitation forecasts in an AI weather model using observational data
11. Wind Speed and Direction Estimation in Japan Based on Pressure-Gradient Interpolation and Geostrophic Wind Approximation
12. TF-STNet: A Time–Frequency Dual-Branch Spatiotemporal Network for NWP-to-Station Bias Correction
13. Statistical versus machine learning-based spatial interpolation of post-processed ensemble weather forecasts
14. Object‐based deep learning for probabilistic convective‐core nowcasting from satellite data
15. STAMP-GAN: A Spatiotemporal Attention-Modulated Generative Adversarial Network for Precipitation Nowcasting
16. A multi‐scale loss formulation for learning a probabilistic model with proper score optimisation
17. CGD-Net: cloud-gated dual-head reconstruction with SAR-temporal guidance for Sentinel-2 cloud removal
18. From Nowcasting to Forecasting: Adapting a Reanalysis-Trained
19. Exploring the role of input data on hail nowcast skill using spatiotemporal neural networks
20. SFNL-Former: A Novel Spatial-Frequency Non-local Network for Precipitation Forecast