A new attention mechanism adds persistent homology and Euler-based topological structure to time-series models via validation-gated residuals, yielding RMSE reductions of 12.5-47.8% in paired tests on synthetic and real datasets when geometry is predictive.
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Global and Local Topology-Aware Attention with Persistent Homology and Euler Biases for Time-Series Forecasting
A new attention mechanism adds persistent homology and Euler-based topological structure to time-series models via validation-gated residuals, yielding RMSE reductions of 12.5-47.8% in paired tests on synthetic and real datasets when geometry is predictive.