mailitics

Tag: path

  • Novelty detection on path space

    Novelty detection on path space arXiv:2512.03243v1 Announce Type: new Abstract: We frame novelty detection on path space as a hypothesis testing problem with signature-based test statistics. Using transportation-cost inequalities of Gasteratos and Jacquier (2023), we obtain tail bounds for false positive rates that extend beyond Gaussian measures to laws of RDE solutions with smooth bounded…

  • Semi-parametric Functional Classification via Path Signatures Logistic Regression

    Semi-parametric Functional Classification via Path Signatures Logistic Regression arXiv:2507.06637v1 Announce Type: new Abstract: We propose Path Signatures Logistic Regression (PSLR), a semi-parametric framework for classifying vector-valued functional data with scalar covariates. Classical functional logistic regression models rely on linear assumptions and fixed basis expansions, which limit flexibility and degrade performance under irregular sampling. PSLR overcomes…

  • Scalable Machine Learning Algorithms using Path Signatures

    Scalable Machine Learning Algorithms using Path Signatures arXiv:2506.17634v1 Announce Type: new Abstract: The interface between stochastic analysis and machine learning is a rapidly evolving field, with path signatures – iterated integrals that provide faithful, hierarchical representations of paths – offering a principled and universal feature map for sequential and structured data. Rooted in rough path…

  • Path Gradients after Flow Matching

    Path Gradients after Flow Matching arXiv:2505.10139v1 Announce Type: new Abstract: Boltzmann Generators have emerged as a promising machine learning tool for generating samples from equilibrium distributions of molecular systems using Normalizing Flows and importance weighting. Recently, Flow Matching has helped speed up Continuous Normalizing Flows (CNFs), scale them to more complex molecular systems, and minimize…

  • Communities in the Kuramoto Model: Dynamics and Detection via Path Signatures

    Communities in the Kuramoto Model: Dynamics and Detection via Path Signatures arXiv:2503.17546v1 Announce Type: new Abstract: The behavior of multivariate dynamical processes is often governed by underlying structural connections that relate the components of the system. For example, brain activity which is often measured via time series is determined by an underlying structural graph, where…