3 citations · 5 across the 6 of their papers we have counts for
4 papers · 1 filter
Diagnostic Tools for Extreme Value Regression Models
Ed Mackay, Jordan Richards, Philip Jonathan
Visual and quantitative goodness-of-fit diagnostics are an important tool in the practitioner's toolbox. The need for convincing and reliable diagnostics is particularly clear when…
Generative modelling of multivariate geometric extremes using normalising flows
Lambert De Monte, Raphaël Huser, Ioannis Papastathopoulos +1
Leveraging the recently emerging geometric approach to multivariate extremes and the flexibility of normalising flows on the hypersphere, we propose a principled deep-learning-base…
Semi-parametric bulk and tail regression using spline-based neural networks
Reetam Majumder, Jordan Richards
Semi-parametric quantile regression (SPQR) is a flexible approach to density regression that learns a spline-based representation of conditional density functions using neural netw…
Deep Learning of Multivariate Extremes via a Geometric Representation
Callum J. R. Murphy-Barltrop, Reetam Majumder, Jordan Richards
The study of geometric extremes, where extremal dependence properties are inferred from the deterministic limiting shapes of scaled sample clouds, provides an exciting approach to…