The Sinkhorn treatment effect is a new entropic optimal transport measure of divergence between counterfactual distributions that admits first- and second-order pathwise differentiability, debiased estimators, and asymptotically valid tests for distributional treatment effects.
Stochastic analysis, filtering, and stochastic optimization , PAGES =
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A deep learning dynamic programming scheme prices path-dependent convertible bonds under GBM, CEV and Heston dynamics, showing that reset and call clauses dominate the underlying process in determining value and that downward resets can paradoxically lower bond prices.
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.
citing papers explorer
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Sinkhorn Treatment Effects: A Causal Optimal Transport Measure
The Sinkhorn treatment effect is a new entropic optimal transport measure of divergence between counterfactual distributions that admits first- and second-order pathwise differentiability, debiased estimators, and asymptotically valid tests for distributional treatment effects.
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A deep learning approach for pricing convertible bonds with path-dependent reset and call provisions
A deep learning dynamic programming scheme prices path-dependent convertible bonds under GBM, CEV and Heston dynamics, showing that reset and call clauses dominate the underlying process in determining value and that downward resets can paradoxically lower bond prices.
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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.