dagnet

My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!

:basketball::robot::basketball: AI web app and API to analyze basketball shots and shooting pose.

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).

Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)

AI Basketball Referee

B站GNN教程资料

Repository which contains various scripts and work with various basketball statistics

Multi-turn dialogue baselines written in PyTorch

DeepShot是一个机器学习模型，它利用高级的球队数据和滚动平均值来预测NBA比赛结果。它结合了历史表现趋势和比赛背景数据，从而提供高度准确的胜率预测（66.45%）。

Code and Content for Manning Publication on Graph Neural Networks