Stéphane Bressan — accepted AI-conference papers

2024

Learning multivariate temporal point processes via the time-change theorem

Guilherme Augusto Zagatti, See Kiong Ng, Stéphane Bressan

AISTATS 2024poster

Marked temporal point processes (TPPs) are a class of stochastic processes that describe the occurrence of a countable number of marked events over continuous time. In machine learning, the most common representation of marked TPPs is the univariate TPP coupled with a conditional mark distribution.…

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2023

COOL, a Context Outlooker, and Its Application to Question Answering and Other Natural Language Processing Tasks

Fangyi Zhu, See-Kiong Ng, Stéphane Bressan

IJCAI 2023poster

Vision outlooker improves the performance of vision transformers, which implements a self-attention mechanism by adding an outlook attention, a form of local attention. In natural language processing, as has been the case in computer vision and other domains, transformer-based models constitute…

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