Temporal Fusion Transformer (Lim et al. 2021) vs 3-XGBoost multi-horizon stack

Built a Temporal Fusion Transformer (TFT, Lim et al. arXiv:1912.09363) over the same 38-feature country-day panel that powers our XGBoost forecast. Single attention-based pass predicts a 30-day p10/p50/p90 trajectory, replacing 3 independent GBMs + a Gaussian conformal wrapper. Trained on CPU within a 60-minute budget (hidden=8, 1 attention head, quantile loss over 0.1/0.5/0.9). LOCO median AUC vs the 7-day XGBoost baseline (0.9236) is published inline at /v1/forecast/tft/info. Honest caveats inline: quantile collapse on rare positives, small 21-country corpus, CPU budget. Shipped as a research second opinion, NOT a production replacement — the headline 7-day forecast still flows through /v1/forecast/{cc}/7day.