3 papers
cs.AI2025
KANFormer for Predicting Fill Probabilities via Survival Analysis in Limit Order Books
Jinfeng Zhong, Emmanuel Bacry, Agathe Guilloux +1
This paper introduces KANFormer, a novel deep-learning-based model for predicting the time-to-fill of limit orders by leveraging both market- and agent-level information. KANFormer…
stat.ME2024
An efficient joint model for high dimensional longitudinal and survival data via generic association features
Van Tuan Nguyen, Adeline Fermanian, Agathe Guilloux +4
This paper introduces a prognostic method called FLASH that addresses the problem of joint modelling of longitudinal data and censored durations when a large number of both longitu…
stat.ML2024
On the Generalization and Approximation Capacities of Neural Controlled Differential Equations
Linus Bleistein, Agathe Guilloux
Neural Controlled Differential Equations (NCDEs) are a state-of-the-art tool for supervised learning with irregularly sampled time series (Kidger, 2020). However, no theoretical an…