activity
20192021
most citedA framework for fostering transparency in shared artificial intelligence models by increasing visibility of contributions

18 citations · 30 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SD2021★ 2 cited

Using DeepProbLog to perform Complex Event Processing on an Audio Stream

Marc Roig Vilamala, Tianwei Xing, Harrison Taylor +6

In this paper, we present an approach to Complex Event Processing (CEP) that is based on DeepProbLog. This approach has the following objectives: (i) allowing the use of subsymboli…

cs.AI2021★ 18 cited

A framework for fostering transparency in shared artificial intelligence models by increasing visibility of contributions

Iain Barclay, Harrison Taylor, Alun Preece +3

Increased adoption of artificial intelligence (AI) systems into scientific workflows will result in an increasing technical debt as the distance between the data scientists and eng…

cs.AI2020★ 2 cited

An Experimentation Platform for Explainable Coalition Situational Understanding

Katie Barrett-Powell, Jack Furby, Liam Hiley +8

We present an experimentation platform for coalition situational understanding research that highlights capabilities in explainable artificial intelligence/machine learning (AI/ML)…

cs.AI2020★ 1 cited

A Hybrid Neuro-Symbolic Approach for Complex Event Processing

Marc Roig Vilamala, Harrison Taylor, Tianwei Xing +6

Training a model to detect patterns of interrelated events that form situations of interest can be a complex problem: such situations tend to be uncommon, and only sparse data is a…

cs.LG2019★ 7 cited

Discriminating Spatial and Temporal Relevance in Deep Taylor Decompositions for Explainable Activity Recognition

Liam Hiley, Alun Preece, Yulia Hicks +2

Current techniques for explainable AI have been applied with some success to image processing. The recent rise of research in video processing has called for similar work n deconst…