Abstract: Deep learning compilers optimize DNN program execution by capturing them as operator-based computation graphs. However, developers’ deep learning programs often contain complex Python ...

Abstract: This paper proposes a subgraph-aware classification framework that integrates efficient frequent subgraph mining with graph neural networks (GNNs) to address the limitations of existing GNNs ...

Ingest, extract, and classify content from a high volume of assets to gain deeper insights and generate relevant suggestions for quick and easy reasoning. This enables the ability to conduct ...