Official implementation of "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training" - xiexi51/MaxK-GNN ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

The goal of few-shot image classification is to learn a classifier that can be well generalized to the unseen classes with a few available labeled samples. One major challenge for few-shot learning is ...

The structure of roads plays an important role in designing autonomous driving algorithms. We propose a novel road graph based driving framework, named RIANet++. The proposed framework considers the ...

This contains examples, scripts and code related to image classification using TensorFlow models (from here) converted to TensorRT. Converting TensorFlow models to TensorRT offers significant ...