In this talk, I will discuss the development of interpretable machine learning models to test scientific hypotheses, with a specific focus on spinal motor control. Voluntary movement requires ...
In finance, data is often incomplete because the data is unavailable, inapplicable or unreported. Unfortunately, many classical data analysis techniques — for instance, linear regression — cannot ...
The lectures on this page should be watched before the live sessions on Monday, June 13, 2022 (Tuesday, June 14 in some time zones). Total viewing time for this lecture series is 2 hours 16 minutes.
In this paper, we propose a latent variable credit risk model for large loan port- folios. It employs the concept of nested Archimedean copulas to account for both a sector-type dependence structure ...
Dynamical systems modeling is one of the most successfully implemented methodologies throughout mathematical oncology (1). Applications of these model first approaches have led to important insights ...
Combining inverse-probability weighting based on propensity scores and a semiparametric outcome model with a latent-class variable as an intervening variable, this paper introduces extensions of Rubin ...
Stochastic loss given default and exposure at default in a structural model of portfolio credit risk
In this paper, we develop a factor-type latent variable model for portfolio credit risk that accounts for stochastically dependent probability of default (PD), loss given default (LGD) and exposure at ...
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