Bitcoin transaction graphs: training, labelled entities, and CoinJoins
Address-transaction graphs for machine learning on Bitcoin: training graphs with CSV node features, edge features and heuristic clustering labels, plus per-transaction subgraphs with known entity labels and CoinJoin subgraphs as Parquet tables with JSON metadata. Built by the authors from blockchain data and address-clustering heuristics as companion data for a graph neural network clustering method. Useful for training and benchmarking address clustering; heuristic labels may wrongly merge distinct users.