PLACE delivers a closed-form certified classification method for point clouds and graphs based on persistent homology with explicit excess-risk bounds, selection rules, and training-time certificates.
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Conformal Seasonal Pools is a training-free method that outperforms DeepNPTS on CRPS, quantile loss, and especially 95% coverage (0.89 vs 0.66) across six time-series datasets while being over 500x faster on CPU.
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A Closed-Form Persistence-Landmark Pipeline for Certified Point-Cloud and Graph Classification
PLACE delivers a closed-form certified classification method for point clouds and graphs based on persistent homology with explicit excess-risk bounds, selection rules, and training-time certificates.
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Training-Free Probabilistic Time-Series Forecasting with Conformal Seasonal Pools
Conformal Seasonal Pools is a training-free method that outperforms DeepNPTS on CRPS, quantile loss, and especially 95% coverage (0.89 vs 0.66) across six time-series datasets while being over 500x faster on CPU.