A 股排序研究双语工作台。GPU 深度模型为 PyTorch 多任务神经网络（VCformer-TPA）：融合序列分解、频域注意力、Transformer 与多尺度卷积，从历史量价特征学习股票排序和未来风险，GPU 用于加速训练。另含 PCA 岭回归、科学抽样、1/3/5 日对照及成本回撤分析。Research prototype; not a live-trading system.
☆22Sep 21, 2026Updated 2 weeks ago
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