Reproducible Python time-series forecasting benchmark with walk-forward validation, leakage-safe backtesting, classical models, lag-based machine learning, tests, and CI.
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Updated
Aug 1, 2026 - Jupyter Notebook
Reproducible Python time-series forecasting benchmark with walk-forward validation, leakage-safe backtesting, classical models, lag-based machine learning, tests, and CI.
Lean 4 formal verification of the exact heterogeneity threshold for stationary covariance-volume enhancement in coupled Ornstein–Uhlenbeck systems.
Reproducible benchmark of urban settlement indices across Sentinel-2, Landsat-8, and VIIRS using SeasoNet and ROI experiments.
Interpretable ML workflow (RBBR) applied to open medical datasets — preprocessing, training, and evaluation scripts for reproducible clinical risk modeling.
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