BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...

It enables model optimization, quantization, graph compilation and conversion, and generates efficient source code. RUHMI provides native support for machine-learning AI frameworks such as ...

Graph polynomials serve as robust algebraic encodings of the intricate combinatorial properties inherent to graphs. At the heart of this discipline lies the Tutte polynomial, an invariant that not ...

Learn and revise how to plot coordinates and create straight line graphs to show the relationship between two variables with GCSE Bitesize Edexcel Maths.

Graph representation learning has re-emerged as a fascinating research topic due to the successful application of graph convolutional networks (GCNs) for graphs and inspires various downstream tasks, ...

The Graph Isomorphism problem regained interest with the rise of Graph Neural Networks (GNN). These GNN models have limited ability to distinguish between isomorphic graphs and hence their outputs are ...

Update olive/passes/onnx/hqq_quantization.py to use onnx_ir for graph manipulation. You can use olive/passes/onnx/rtn_quantization.py as a reference. Be sure to ...

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