activity
20232025
most citedRS-Mamba for Large Remote Sensing Image Dense Prediction

7 citations · 37 across the 12 of their papers we have counts for

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Showing cs.LGShow all

11 papers · 1 filter

cs.LG2025

VQLTI: Long-Term Tropical Cyclone Intensity Forecasting with Physical Constraints

Xinyu Wang, Lei Liu, Kang Chen +3

Tropical cyclone (TC) intensity forecasting is crucial for early disaster warning and emergency decision-making. Numerous researchers have explored deep-learning methods to address…

cs.LG20243 cited

FengWu-W2S: A deep learning model for seamless weather-to-subseasonal forecast of global atmosphere

Fenghua Ling, Kang Chen, Jiye Wu +4

Seamless forecasting that produces warning information at continuum timescales based on only one system is a long-standing pursuit for weather-climate service. While the rapid adva…

cs.LG2024

Benchmarking AI-based data assimilation to advance data-driven global weather forecasting

Wuxin Wang, Weicheng Ni, Ben Fei +7

Research on Artificial Intelligence (AI)-based Data Assimilation (DA) is expanding rapidly. However, the absence of an objective, comprehensive, and real-world benchmark hinders th…

cs.LG20241 cited

FNP: Fourier Neural Processes for Arbitrary-Resolution Data Assimilation

Kun Chen, Tao Chen, Peng Ye +5

Data assimilation is a vital component in modern global medium-range weather forecasting systems to obtain the best estimation of the atmospheric state by combining the short-term…

cs.LG2024

Benchmarking Physics-Informed Time-Series Models for Operational Global Station Weather Forecasting

Tao Han, Zhibin Wen, Zhenghao Chen +3

The development of Time-Series Forecasting (TSF) models is often constrained by the lack of comprehensive datasets, especially in Global Station Weather Forecasting (GSWF), where e…

cs.LG20241 cited

CRA5: Extreme Compression of ERA5 for Portable Global Climate and Weather Research via an Efficient Variational Transformer

Tao Han, Zhenghao Chen, Song Guo +2

The advent of data-driven weather forecasting models, which learn from hundreds of terabytes (TB) of reanalysis data, has significantly advanced forecasting capabilities. However,…