5 papers
Split Conformal Prediction under Data Contamination
Jase Clarkson, Wenkai Xu, Mihai Cucuringu +2
Conformal prediction is a non-parametric technique for constructing prediction intervals or sets from arbitrary predictive models under the assumption that the data is exchangeable…
Stein's method for distributions modelling competing and complementary risk problems
Anum Fatima, Gesine Reinert
Competing and Complementary risk (CCR) problems are often modelled using a class of distributions of the maximum, or minimum, of a random number of i.i.d. random variables; we call…
Normal approximation for the posterior in exponential families
Adrian Fischer, Robert E. Gaunt, Gesine Reinert +1
In this paper, we obtain quantitative, non-asymptotic, and data-dependent \textit{Bernstein-von Mises type} bounds on the normal approximation of the posterior distribution in expo…
Generalization Error of Graph Neural Networks in the Mean-field Regime
Gholamali Aminian, Yixuan He, Gesine Reinert +2
This work provides a theoretical framework for assessing the generalization error of graph neural networks in the over-parameterized regime, where the number of parameters surpasse…
Co-trading networks for modeling dynamic interdependency structures and estimating high-dimensional covariances in US equity markets
Yutong Lu, Gesine Reinert, Mihai Cucuringu
The time proximity of trades across stocks reveals interesting topological structures of the equity market in the United States. In this article, we investigate how such concurrent…