“Training on large graph-structured datasets poses unique system challenges, demanding optimizations for sparse operations and inter-node communication. We hope the addition of a GNN based benchmark ...
Adapting to the Stream: An Instance-Attention GNN Method for Irregular Multivariate Time Series Data
DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification ...
A new technical paper titled “TROJAN-GUARD: Hardware Trojans Detection Using GNN in RTL Designs” was published by researchers at University of Connecticut and University of Minnesota. “hip ...
The demand for immersive, realistic graphics in mobile gaming and AR or VR is pushing the limits of mobile hardware. Achieving lifelike simulations of fluids, cloth, and other materials historically ...
Supply chain data has been studied as a potential source of investment opportunity for years. Many possible theoretical approaches can be employed when considering how an investor could leverage ...
SAN FRANCISCO--(BUSINESS WIRE)--Today, MLCommons ® announced new results for the MLPerf ® Training v4.0 benchmark suite, including first-time results for two benchmarks: LoRA fine-tuning of LLama 2 ...
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