pyscf-ipu

??An Easy-to-use and Fast Deep Learning Model Deployment Toolkit for ??Cloud ?Mobile and ?Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models with end-to-end optimization, multi-platform and multi-framework support.

? Accelerate inference and training of ? Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools

An Industrial Graph Neural Network Framework

An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)

DCT (discrete cosine transform) functions for pytorch

Code and resources on scalable and efficient Graph Neural Networks (TNNLS 2023)

A PyTorch Graph Neural Network Library

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

1. Use BERT, ALBERT and GPT2 as tensorflow2.0's layer. 2. Implement GCN, GAN, GIN and GraphSAGE based on message passing.