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Tag: signature

  • The Volterra signature

    The Volterra signature arXiv:2603.04525v1 Announce Type: new Abstract: Modern approaches for learning from non-Markovian time series, such as recurrent neural networks, neural controlled differential equations or transformers, typically rely on implicit memory mechanisms that can be difficult to interpret or to train over long horizons. We propose the Volterra signature $mathrm{VSig}(x;K)$ as a principled, explicit…

  • Signature Kernel Scoring Rule as Spatio-Temporal Diagnostic for Probabilistic Forecasting

    Signature Kernel Scoring Rule as Spatio-Temporal Diagnostic for Probabilistic Forecasting arXiv:2510.19110v1 Announce Type: new Abstract: Modern weather forecasting has increasingly transitioned from numerical weather prediction (NWP) to data-driven machine learning forecasting techniques. While these new models produce probabilistic forecasts to quantify uncertainty, their training and evaluation may remain hindered by conventional scoring rules, primarily MSE,…

  • Learning with Expected Signatures: Theory and Applications

    Learning with Expected Signatures: Theory and Applications arXiv:2505.20465v1 Announce Type: new Abstract: The expected signature maps a collection of data streams to a lower dimensional representation, with a remarkable property: the resulting feature tensor can fully characterize the data generating distribution. This “model-free” embedding has been successfully leveraged to build multiple domain-agnostic machine learning (ML)…

  • Power Spectrum Signatures of Graphs

    Power Spectrum Signatures of Graphs arXiv:2503.09660v1 Announce Type: new Abstract: Point signatures based on the Laplacian operators on graphs, point clouds, and manifolds have become popular tools in machine learning for graphs, clustering, and shape analysis. In this work, we propose a novel point signature, the power spectrum signature, a measure on $mathbb{R}$ defined as…