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From the 2 of 34 linked papers with an AI index.

activity
20242026
most citedA Self-Evolving AI Agent System for Climate Science

3 citations · 4 across the 22 of their papers we have counts for

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Showing cs.LGShow all

11 papers · 1 filter

cs.LG2026

UniPolymer: A Unified Framework for Property Prediction, Structure Recommendation, and Evaluation in Polyimide Design

Junquan Hu, Zhihui Wang, Peng Xu +4

Designing polyimide structures with specific glass transition temperatures (Tg) is highly challenging. Existing methods primarily focus on target-conditioned generation, lacking an…

cs.LG2026

TSSM: Triaxial State Space Model for Global Station Weather Forecasting with Temporal-Variable-Historical Modeling

Songru Yang, Zili Liu, Tao Han +7

The paper introduces a Triaxial State Space Model that leverages period‑aligned historical weather data and a temporal‑variable‑historical paradigm to improve global station weathe…

cs.LG2026

Learning more physically realistic dynamics in machine-learning based weather forecasting with latent-space constraints

Hang Fan, Yi Xiao, Yongquan Qu +5

Data-driven machine learning (ML) models are reshaping weather forecasting and have shown the potential to accelerate and surpass traditional physics-based approaches, leading to a…

cs.LG2026

Accurate and Efficient Hybrid-Ensemble Atmospheric Data Assimilation in Latent Space with Uncertainty Quantification

Hang Fan, Juan Nathaniel, Yi Xiao +5

Data assimilation (DA) combines model forecasts and observations to estimate the optimal state of the atmosphere with its uncertainty, providing initial conditions for weather pred…

cs.LG2026

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.LG20261 cited

XiChen: A global weather observation-to-forecast machine learning system via four-dimensional variational gradient-guided flexible assimilation

Wuxin Wang, Weicheng Ni, Lilan Huang +13

Machine Learning (ML) has shown great promise in revolutionizing weather forecasting, yet most ML systems still rely on initial conditions generated by Numerical Weather Prediction…