Derives non-asymptotic MSE bounds separating discretization and fluctuation errors for expected signature estimation via block averaging under weak dependence for rough paths.
Uniqueness for the signature of a path of bounded variation and the reduced path group.Annals of Mathematics, 171(1):109–167
2 Pith papers cite this work. Polarity classification is still indexing.
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Semi-supervised Bayesian GANs with log-signatures for uncertainty-aware credit card fraud detection show consistent improvements over benchmarks on the BankSim simulator under varying label proportions.
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Finite-Sample Bounds for Expected Signature Estimation under Weak Dependence
Derives non-asymptotic MSE bounds separating discretization and fluctuation errors for expected signature estimation via block averaging under weak dependence for rough paths.
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Semi-Supervised Bayesian GANs with Log-Signatures for Uncertainty-Aware Credit Card Fraud Detection
Semi-supervised Bayesian GANs with log-signatures for uncertainty-aware credit card fraud detection show consistent improvements over benchmarks on the BankSim simulator under varying label proportions.