1 citations · 1 across the 3 of their papers we have counts for
4 papers
Signature Maximum Mean Discrepancy Two-Sample Statistical Tests
Andrew Alden, Blanka Horvath, Zacharia Issa
Maximum Mean Discrepancy (MMD) is a widely used concept in machine learning research which has gained popularity in recent years as a highly effective tool for comparing (finite-di…
Non-parametric online market regime detection and regime clustering for multidimensional and path-dependent data structures
Zacharia Issa, Blanka Horvath
In this work we present a non-parametric online market regime detection method for multidimensional data structures using a path-wise two-sample test derived from a maximum mean di…
Non-adversarial training of Neural SDEs with signature kernel scores
Zacharia Issa, Blanka Horvath, Maud Lemercier +1
Neural SDEs are continuous-time generative models for sequential data. State-of-the-art performance for irregular time series generation has been previously obtained by training th…
Clustering Market Regimes using the Wasserstein Distance
Blanka Horvath, Zacharia Issa, Aitor Muguruza
The problem of rapid and automated detection of distinct market regimes is a topic of great interest to financial mathematicians and practitioners alike. In this paper, we outline…