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Level up your LLM speed and efficiency

Deploying large language models can be slow and costly, but smart optimization changes that. From GPU memory tricks to hybrid CUDA graph execution, new methods are slashing latency and boosting ...
EurekAlert!

Real-time, large-scale graph neural network inference through BingoCGN

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...
News Medical

Advancing gene regulatory network inference with causal discovery and graph neural networks

Gene regulatory networks (GRNs) depict the regulatory mechanisms of genes within cellular systems as a network, offering vital insights for understanding cell processes and molecular interactions that ...
mccormick.northwestern.edu

MLDS 490: Bayesian Methods for Inference and Decision Making

This course offers a rigorous yet practical exploration of Bayesian reasoning for data-driven inference and decision-making. Students will gain a deep understanding of probabilistic modeling, and ...
동아사이언스

Adaptive Semiconductor Resolves Bottleneck in AI Graph Data Processing

'Graph Neural Networks (GNNs)' are an AI technology used to analyze complex relationships, such as those needed for YouTube video recommendations. A South Korean research team has developed a ...