Abstract: Graph Contrastive Learning (GCL) has significantly advanced graph representation learning by generating more effective node embeddings. It aims to create informative representations by ...

The Scenario Runner is an application that executes shader and neural network graph workloads through Vulkan® or the ML extensions for Vulkan®. The Scenario Runner acts as a validation and performance ...

Abstract: Graph Transformers, emerging as a new architecture for graph representation learning, suffer from the quadratic complexity and can only handle graphs with at most thousands of nodes. To this ...

Recent augmentation-based methods showed that message-passing (MP) neural networks often perform poorly on low-degree nodes, leading to degree biases due to a lack of messages reaching low-degree ...