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Found 9 papers, 1 papers with code
Tighter Generalization Bounds on Digital Computers via Discrete Optimal Transport
Notably, $c_{m}\in \mathcal{O}(\sqrt{m})$ for learning models on discretized Euclidean domains.
Estimating Barycenters of Distributions with Neural Optimal Transport
Given a collection of probability measures, a practitioner sometimes needs to find an "average" distribution which adequately aggregates reference distributions.
Calibration of the Bass Local Volatility model
The Bass local volatility model introduced by Backhoff-Veraguas--Beiglb\"ock--Huesmann--K\"allblad is a Markov model perfectly calibrated to vanilla options at finitely many maturities, that approximates the Dupire local volatility model.
Energy-Guided Continuous Entropic Barycenter Estimation for General Costs
Optimal transport (OT) barycenters are a mathematically grounded way of averaging probability distributions while capturing their geometric properties.
Quantitative Fundamental Theorem of Asset Pricing
In this paper we provide a quantitative analysis to the concept of arbitrage, that allows to deal with model uncertainty without imposing the no-arbitrage condition.
Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer
Several problems in stochastic analysis are defined through their geometry, and preserving that geometric structure is essential to generating meaningful predictions.
From Bachelier to Dupire via Optimal Transport
Famously mathematical finance was started by Bachelier in his 1900 PhD thesis where - among many other achievements - he also provides a formal derivation of the Kolmogorov forward equation.
Disease Momentum: Estimating the Reproduction Number in the Presence of Superspreading
Our models demonstrate that the estimation uncertainty of the reproduction number increases with superspreading and that this improves the performance of prediction intervals.
Stability of martingale optimal transport and weak optimal transport
Under mild regularity assumptions, the transport problem is stable in the following sense: if a sequence of optimal transport plans $\pi_1, \pi_2, \ldots$ converges weakly to a transport plan $\pi$, then $\pi$ is also optimal (between its marginals).
Probability Mathematical Finance
