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A Kolmogorov–Arnold Neural Model for Cascading Extremes
作者Miguel de Carvalho; Clemente Ferrer; Ronny Vallejos
作者单位1. School of Mathematics, University of Edinburgh, Edinburgh, UK; 2. Department of Mathematics, University of Aveiro, Aveiro, Portugal; 3. Faculty of Mathematics, Pontificia Universidad Católica de Chile, Santiago, Chile; 4. Department of Mathematics, Universidad Técnica Federico Santa María, Valparaíso, Chile
Weak signals and heavy tails: learning theory meets extreme value analysis
作者Stephan Clémençon; Anne Sabourin
作者单位1. LTCI, Télécom Paris, Institut polytechnique de Paris, Palaiseau, France; 2. Université Paris Cité, Université Paris Saclay, ENS Paris Saclay, CNRS, SSA, INSERM, Centre Borelli, Paris, France
Extreme conformal prediction: Reliable intervals for high-impact events
作者Olivier C. Pasche; Henry Lam; Sebastian Engelke
作者单位1. Research Institute for Statistics and Information Science, University of Geneva, Geneva, Switzerland; 2. Department of Industrial Engineering and Operations Research, Columbia University, New York, USA
Semi-parametric bulk and tail regression using spline-based neural networks
作者Reetam Majumder; Jordan Richards
作者单位1. Department of Mathematical Sciences, University of Arkansas, Fayetteville, USA; 2. School of Mathematics and Maxwell Institute for Mathematical Sciences, University of Edinburgh, Edinburgh, Scotland
Simulation of multivariate extremes: A Wasserstein–Aitchison GAN approach
作者Stéphane Lhaut; Holger Rootzén; Johan Segers
作者单位1. Institute of Statistics, Biostatistics and Actuarial Sciences, UCLouvain, Louvain-La-Neuve, Belgium; 2. CREST, ENSAE Paris, Palaiseau, France; 3. Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden; 4. Department of Mathematics, KU Leuven, Heverlee, Belgium
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