1 citations · 1 across the 5 of their papers we have counts for
5 papers
Variational Inference for Lévy Process-Driven SDEs via Neural Tilting
Yaman Kindap, Manfred Opper, Benjamin Dupuis +2
Modelling extreme events and heavy-tailed phenomena is central to building reliable predictive systems in domains such as finance, climate science, and safety-critical AI. While Lé…
Generalised Hyperbolic State-space Models for Inference in Dynamic Systems
Yaman Kındap, Simon Godsill
In this work we study linear vector stochastic differential equation (SDE) models driven by the generalised hyperbolic (GH) Lévy process for inference in continuous-time non-Gaussi…
Point process simulation of generalised hyperbolic Lévy processes
Yaman Kindap, Simon Godsill
Generalised hyperbolic (GH) processes are a class of stochastic processes that are used to model the dynamics of a wide range of complex systems that exhibit heavy-tailed behavior,…
Non-Gaussian Process Regression
Yaman Kındap, Simon Godsill
Standard GPs offer a flexible modelling tool for well-behaved processes. However, deviations from Gaussianity are expected to appear in real world datasets, with structural outlier…
Point process simulation of generalised inverse Gaussian processes and estimation of the Jaeger integral
Simon Godsill, Yaman Kındap
In this paper novel simulation methods are provided for the generalised inverse Gaussian (GIG) Lévy process. Such processes are intractable for simulation except in certain special…