94 citations · 133 across the 33 of their papers we have counts for
40 papers
Consistent community recovery in stochastic block Ornstein-Uhlenbeck processes
Anders Norlyk, Almut E. D. Veraart
We propose the stochastic block Ornstein-Uhlenbeck (SBOU) process, a continuous-time multivariate model in which the drift matrix encodes a latent group structure among its compone…
Edge-indexed network time series with graph Ornstein-Uhlenbeck dynamics
Jiaming Chen, Almut E. D. Veraart
We introduce a class of Lévy-driven graph Ornstein-Uhlenbeck (grOU) models for edge-indexed network time series. The proposed framework extends generalized network autoregressive (…
Simulation-based inference via telescoping ratio estimation for trawl processes
Dan Leonte, Raphaël Huser, Almut E. D. Veraart
The growing availability of large and complex datasets has increased interest in temporal stochastic processes that can capture stylized facts such as marginal skewness, non-Gaussi…
Causal tail coefficient for compound extremes in multivariate time series
Cathy Yin, Adam M. Sykulski, Almut E. D. Veraart
Extreme events are often multivariate in nature. A compound extreme occurs when a combination of variables jointly produces a significant impact, even if individual components are…
Learning with Expected Signatures: Theory and Applications
Lorenzo Lucchese, Mikko S. Pakkanen, Almut E. D. Veraart
The expected signature maps a collection of data streams to a lower dimensional representation, with a remarkable property: the resulting feature tensor can fully characterize the…
The Markov approximation of the periodic multivariate Poisson autoregression
Mahmoud Khabou, Edward A. K. Cohen, Almut E. D. Veraart
This paper introduces a periodic multivariate Poisson autoregression with potentially infinite memory, with a special focus on the network setting. Using contraction techniques, we…