arXiv subjects

Isabella Deutsch

Publications and source records attributed to Isabella Deutsch.

4 recordsLinked to original sources

arXiv2026

The Ancestor Hawkes Process with an Application to Group Chat Data

The Hawkes process is used to model point process data where events occur in clusters and bursts. In a standard multivariate Hawkes process, every event that occurs in a dimension has an equal impact on the process intensity. However, this assumption is unrealistic in applications such as the modelling of message cascades where the effect of an event depends on whether it was the initiator or a member of a particular cluster. To alleviate this, we introduce a new Hawkes process model, the Ancestor Hawkes process, which allows the impact of each event to vary based on its origin. The relevance of the Ancestor Hawkes process is showcased on real data from a 9-person group chat, where our proposed approach reveals individual response preferences. Crucially, this is achieved in a privacy-conscious manner, as only the sender and the time at which a message was sent -- but not its content -- are utilised. These nuances of messaging cascades are missed by the standard Hawkes process, but are relevant for studying latent interaction structure and for personalised notification management.

stat.ME↗

arXiv2023

Estimating Product Cannibalisation in Wholesale using Multivariate Hawkes Processes with Inhibition

Product cannibalisation in the marketplace refers to the decrease in the sales of one product due to competition from another product. We examine this phenomenon in a wholesale data set provided by an international company. We use a multivariate Hawkes process where each product is represented by a dimension, with cross-inhibition effects that model product cannibalisation. To implement the Hawkes process with inhibition we resolve challenges regarding the integration of the intensity function and introduce a new, stronger conditions for stability as existing conditions are unnecessarily strict under inhibition. We conduct our analysis in a Bayesian framework, for which we design a dimension-independent prior on the cross-inhibition based on a reparametrisation.

stat.AP↗

arXiv2022

An English translation of A. Wiman's "On the algebraic curves of genus $p=4$, $5$ and $6$, which posses unambiguous transformations into themselves"

This is an English translation of the paper "Ueber die algebraischen Curven von den Geschlechtern $p = 4$, $5$ und $6$, welche eindeutigen Transformationen in sich besitzen" by Anders Wiman, Bihang till Kongl. Svenska vetenskaps-akademiens handlingar 21 (1895): 1-41. The article, originally written in German, classifies non-hyperelliptic curves which have non-trivial automorphism groups via classical methods in algebraic geometry.

math.AG↗

arXiv2021

ABC Learning of Hawkes Processes with Missing or Noisy Event Times

The self-exciting Hawkes process is widely used to model events which occur in bursts. However, many real world data sets contain missing events and/or noisily observed event times, which we refer to as data distortion. The presence of such distortion can severely bias the learning of the Hawkes process parameters. To circumvent this, we propose modeling the distortion function explicitly. This leads to a model with an intractable likelihood function which makes it difficult to deploy standard parameter estimation techniques. As such, we develop the ABC-Hawkes algorithm which is a novel approach to estimation based on Approximate Bayesian Computation (ABC) and Markov Chain Monte Carlo. This allows the parameters of the Hawkes process to be learned in settings where conventional methods induce substantial bias or are inapplicable. The proposed approach is shown to perform well on both real and simulated data.

stat.AP↗