Post #378

Tsinghua University Releases First AutoML Toolkit for Graph Datasets & Tasks At least in the research papers, hyperparameter tuning, feature engineering, architecture and model search, stacking and boosting have been largely ignored and I have a good faith that in the coming year there will be more papers that extensively perform all of those to gain additional boost in performance. This AutoGL PyTorch Framework does just this. It's based off PyG, contains a few standard datasets and models, has several HP algorithms, generates graphlet, pagerank, and other features, stacks models' predictions, and more. Looks very promising.