Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
Abstract: This paper proposes a spatio-temporal graph convolutional network incorporating knowledge graph embeddings for hydrological time series prediction. A knowledge graph is constructed to ...
The Graph offers access to competitive and cost-efficient decentralized data sets. The network boasts a 99.99% uptime and 24/7 availability. Central to The Graph’s operations are subgraphs, APIs that ...
The prediction of the properties of crystal materials has always been a core issue in materials science and solid-state physics. With the rapid development of computer simulation techniques and ...
Abstract: With excellent learning ability, the pretrained large model is challenging the mainstream traffic prediction paradigm. However, the pretraining process of large spatiotemporal models still ...
Nigel Drego, Co-founder and Chief Technology Officer at Quadric, presented the “ONNX and Python to C++: State-of-the-art Graph Compilation” tutorial at this year’s Embedded Vision Summit. Quadric’s ...
We provide script agent_evaluation/eval.py for evaluating the forecasting performance of the LLM agents. It has the same arguments as the react_agent.py and direct_agent.py scripts, with the ...
Many successful machine learning models for molecular property prediction rely on Lewis structure representations, commonly encoded as SMILES strings. However, a key limitation arises with molecules ...
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