L0-zhang

DFCAN-pytorch

Code is basically a pytorch implementation of DFCAN/DFGAN. All credit goes to the authors of DFCAN/DFGAN, listed in the paper“Evaluation and development of deep neural networks for image super-resolution in optical microscopy”.

GAT

Graph classification using GAT on MUTAG dataset

Semantic-Segmentation-for-lane-detection

a-simple-example-for-VOC-mAP

Bayesian-Optimization

simple realization of Bayesian Optimization

DeepLearningDeployment

Examples and tools for deep learning deployment

graph_nets

PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.

knowledge_distill-pytorch-demo-about-mnist

lstm-crf-with-batch_size

tentorrt_demo