Introduces anchored multi-orbit distance-array projections that characterize Furstenberg disjointness via an independence criterion, supported by a marked Gromov-Vershik reconstruction.
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Detecting strange attractors in turbulence
8 Pith papers cite this work, alongside 5,648 external citations. Polarity classification is still indexing.
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UNVERDICTED 8representative citing papers
Martingale Neural Operator uses Doob-Meyer factorization to output mean and low-rank covariance for stochastic PDE terminal laws, achieving large Wasserstein reductions versus diffusion baselines on tested SPDEs.
A novel identity connects reduced-model drift and diffusion to the conditional score of the finite-time transition density, turning calibration into a least-squares problem over stationary lagged pairs that preserves invariant statistics and dynamical correlations.
A kernel-based data-driven optimization method computes optimal perturbations to control the spectrum of transfer operators in high-dimensional dynamical systems.
PIDM-DP integrates Dormand-Prince ODE solving into DDPM denoising with scheduled physics guidance to reconstruct chaotic states, reporting up to 15.4x RMSE gains over baselines on five systems including stiff cases.
A standardized pipeline converts time series to graphs, computes persistence diagrams, and extracts features that classify UCR benchmarks, with diffusion distance outperforming shortest-path metrics and performance varying by graph type.
Short histories of observations can recover the underlying manifold for transporting discontinuous densities when direct source-target pairs are insufficient due to folds or marginalization.
Cardiac Stability Theory derives a composite Cardiac Stability Index from four axioms and transfers an ECG model to smartphone PPG for non-invasive continuous cardiac monitoring.
citing papers explorer
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Observing Joinings: A Distance-Array Characterization of Furstenberg Disjointness
Introduces anchored multi-orbit distance-array projections that characterize Furstenberg disjointness via an independence criterion, supported by a marked Gromov-Vershik reconstruction.
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Martingale Neural Operators: Learning Stochastic Marginals via Doob-Meyer Factorization
Martingale Neural Operator uses Doob-Meyer factorization to output mean and low-rank covariance for stochastic PDE terminal laws, achieving large Wasserstein reductions versus diffusion baselines on tested SPDEs.
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Conditional Score-Based Modeling of Effective Langevin Dynamics
A novel identity connects reduced-model drift and diffusion to the conditional score of the finite-time transition density, turning calibration into a least-squares problem over stationary lagged pairs that preserves invariant statistics and dynamical correlations.
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Data-driven methods for computation of optimal linear response in high-dimensional dynamical systems
A kernel-based data-driven optimization method computes optimal perturbations to control the spectrum of transfer operators in high-dimensional dynamical systems.
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PIDM-DP: Physics-Informed Diffusion with Dormand-Prince Integration for Chaotic System Identification and State Reconstruction across Multiple Dynamical Regimes
PIDM-DP integrates Dormand-Prince ODE solving into DDPM denoising with scheduled physics guidance to reconstruct chaotic states, reporting up to 15.4x RMSE gains over baselines on five systems including stiff cases.
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Persistent Homology of Time Series through Complex Networks
A standardized pipeline converts time series to graphs, computes persistence diagrams, and extracts features that classify UCR benchmarks, with diffusion distance outperforming shortest-path metrics and performance varying by graph type.
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A geometric approach to the transport of discontinuous densities
Short histories of observations can recover the underlying manifold for transporting discontinuous densities when direct source-target pairs are insufficient due to folds or marginalization.
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Cardiac Stability Theory: An Axiomatically Grounded Framework for Continuous Cardiac Health Monitoring via Smartphone Photoplethysmography
Cardiac Stability Theory derives a composite Cardiac Stability Index from four axioms and transfers an ECG model to smartphone PPG for non-invasive continuous cardiac monitoring.