Implementation of the Self-Supervised Spatiotemporal GNN (ST-GNN) for detecting financial contagion and systemic risk using BIS banking data (1977–2023).
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Updated
Jul 7, 2026 - Jupyter Notebook
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bis-data
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Deep learning for systemic financial risk: an Unsupervised Graph Autoencoder and a Spatio-Temporal GNN (GCN+LSTM) trained on 26 years of BIS banking network data (2000–2026) to autonomously detect crises and forecast cross-border exposure shifts — no manual features, no crisis labels.
deep-learning network-science pytorch lstm banking unsupervised-learning spatio-temporal gcn anomaly-detection early-warning-systems time-series-forecasting graph-neural-networks graph-representation-learning systemic-risk pytorch-geometric graph-autoencoder temporal-gnn bis-data financial-learning macroprudential-risk
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Updated
Sep 7, 2026 - Jupyter Notebook
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