2 citations · 6 across the 7 of their papers we have counts for
8 papers
WeatherSyn: An Instruction Tuning MLLM For Weather Forecasting Report Generation
Zinan Zheng, Yang Liu, Nuo Chen +3
Accurate weather forecast reporting enables individuals and communities to better plan daily activities and agricultural operations. However, the current reporting process primaril…
Mesh Interpolation Graph Network for Dynamic and Spatially Irregular Global Weather Forecasting
Zinan Zheng, Yang Liu, Jia Li
Graph neural networks have shown promising results in weather forecasting, which is critical for human activity such as agriculture planning and extreme weather preparation. Howeve…
CirT: Global Subseasonal-to-Seasonal Forecasting with Geometry-inspired Transformer
Yang Liu, Zinan Zheng, Jiashun Cheng +4
Accurate Subseasonal-to-Seasonal (S2S) climate forecasting is pivotal for decision-making including agriculture planning and disaster preparedness but is known to be challenging du…
Graph Pre-Training Models Are Strong Anomaly Detectors
Jiashun Cheng, Zinan Zheng, Yang Liu +5
Graph Anomaly Detection (GAD) is a challenging and practical research topic where Graph Neural Networks (GNNs) have recently shown promising results. The effectiveness of existing…
Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Physical Dynamics Learning
Zinan Zheng, Yang Liu, Jia Li +2
Incorporating Euclidean symmetries (e.g. rotation equivariance) as inductive biases into graph neural networks has improved their generalization ability and data efficiency in unbo…
SimXRD-4M: Big Simulated X-ray Diffraction Data Accelerate the Crystal Symmetry Classification
Bin Cao, Yang Liu, Zinan Zheng +3
Spectroscopic data, particularly diffraction data, contain detailed crystal and microstructure information and thus are crucial for materials discovery. Powder X-ray diffraction (X…
Weakly Supervised Anomaly Detection via Knowledge-Data Alignment
Haihong Zhao, Chenyi Zi, Yang Liu +3
Anomaly detection (AD) plays a pivotal role in numerous web-based applications, including malware detection, anti-money laundering, device failure detection, and network fault anal…
Deep Insights into Noisy Pseudo Labeling on Graph Data
Botao Wang, Jia Li, Yang Liu +4
Pseudo labeling (PL) is a wide-applied strategy to enlarge the labeled dataset by self-annotating the potential samples during the training process. Several works have shown that i…