GlobalSpec

Chapter 5: Statistical Inference Using Factor Graphs

In the previous two chapters we have introduced estimation theory and factor graphs. Although these two topics may seem disparate, they are closely linked. In this chapter we will use factor graphs to ...
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 ...
EurekAlert!

Graph learning and single-cell genomics may unlock more accurate gene regulatory network inference

Overview of the ZINB-GRAN: Starting with the count matrix from scRNA-seq data as input, ZINB-GRAN first constructs a WGCN from gene expression data. Based on this WGCN, it builds an initial regulatory ...
Computer Weekly

Tensordyne co-founder: When it comes to inference, enterprises need more options than ever

Tensordyne is known for hardware and software acceleration platforms designed specifically for training and deploying deep ...
Forbes

The New Frontier Of LLM Inference: Where The Next Tenfold Gains Will Come From

Shakti P. Singh, Principal Engineer at Intuit and former OCI model inference lead, specializing in scalable AI systems and LLM inference. Generative models are rapidly making inroads into enterprise ...
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 ...
EurekAlert!

Gene regulatory network inference based on causal discovery integrating with graph neural network

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 ...