4 papers · 1 filter
Counterfactual Causal Inference in Natural Language with Large Language Models
Gaël Gendron, Jože M. Rožanec, Michael Witbrock +1
Causal structure discovery methods are commonly applied to structured data where the causal variables are known and where statistical testing can be used to assess the causal relat…
Robust Domain Generalisation with Causal Invariant Bayesian Neural Networks
Gaël Gendron, Michael Witbrock, Gillian Dobbie
Deep neural networks can obtain impressive performance on various tasks under the assumption that their training domain is identical to their target domain. Performance can drop dr…
Can Large Language Models Learn Independent Causal Mechanisms?
Gaël Gendron, Bao Trung Nguyen, Alex Yuxuan Peng +2
Despite impressive performance on language modelling and complex reasoning tasks, Large Language Models (LLMs) fall short on the same tasks in uncommon settings or with distributio…
Recurrence over Video Frames (RoVF) for the Re-identification of Meerkats
Mitchell Rogers, Kobe Knowles, Gaël Gendron +7
Deep learning approaches for animal re-identification have had a major impact on conservation, significantly reducing the time required for many downstream tasks, such as well-bein…