output
20222025
most citedOcean Wave Forecasting with Deep Learning as Alternative to Conventional Models

11 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

5 papers

astro-ph.IM2025★ 1 cited

CUBE2: A Parallel -Body Simulation Code for Scalability, Accuracy, and Memory Efficiency

Hao-Ran Yu, Bing-Hang Chen, Kun Xu +4

-body simulation serves as a critical method for modeling cosmic evolution and poses a significant challenge in high-performance computing. We present CUBE2, an open-source cosm…

q-bio.GN2025★ 4 cited

Benchmarking LLM-based agents for single-cell omics analysis

Yang Liu, Lu Zhou, Xiawei Du +4

Background: The surge in single-cell omics data exposes limitations in traditional, manually defined analysis workflows. AI agents offer a paradigm shift, enabling adaptive plannin…

physics.ao-ph2024★ 11 cited

Ocean Wave Forecasting with Deep Learning as Alternative to Conventional Models

Ziliang Zhang, Huaming Yu, Danqin Ren +3

This study presents OceanCastNet (OCN), a machine learning approach for wave forecasting that incorporates wind and wave fields to predict significant wave height, mean wave period…

cond-mat.mtrl-sci2022★ 2 cited

Self-supervised Representations and Node Embedding Graph Neural Networks for Accurate and Multi-scale Analysis of Materials

Jian-Gang Kong, Ke-Lin Zhao, Jian Li +5

Supervised machine learning algorithms, such as graph neural networks (GNN), have successfully predicted material properties. However, the superior performance of GNN usually relie…

cond-mat.mtrl-sci2022★ 9 cited

Self-supervised graph neural networks for accurate prediction of Néel temperature

Jian-Gang Kong, Qing-Xu Li, Jian Li +2

Antiferromagnetic materials are exciting quantum materials with rich physics and great potential for applications. It is highly demanded of the accurate and efficient theoretical m…