Stephen Bonner

According to our database, Stephen Bonner authored at least 35 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

The Role of Graph Topology in the Performance of Biomedical Knowledge Graph Completion Models.

Alberto Cattaneo, Stephen Bonner, Thomas Martynec, Carlo Luschi, Ian P. Barrett, Daniel Justus

CoRR, 2024

2022

A Knowledge Graph-Enhanced Tensor Factorisation Model for Discovering Drug Targets.

Cheng Ye, Rowan Swiers, Stephen Bonner, Ian P. Barrett

IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Implications of topological imbalance for representation learning on biomedical knowledge graphs.

Stephen Bonner, Ufuk Kirik, Ola Engkvist, Jian Tang, Ian P. Barrett

Briefings Bioinform., 2022

A review of biomedical datasets relating to drug discovery: a knowledge graph perspective.

Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, Andreas Bender, Charles Tapley Hoyt, William L. Hamilton

Briefings Bioinform., 2022

A Unified View of Relational Deep Learning for Drug Pair Scoring.

Benedek Rozemberczki, Stephen Bonner, Andriy Nikolov, Michaël Ughetto, Sebastian Nilsson, Eliseo Papa

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

Predicting Potential Drug Targets Using Tensor Factorisation and Knowledge Graph Embeddings.

Cheng Ye, Rowan Swiers, Stephen Bonner, Ian P. Barrett

CoRR, 2021

Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery.

Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, William L. Hamilton

CoRR, 2021

A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective.

Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, Andreas Bender, William L. Hamilton

CoRR, 2021

Camera Bias in a Fine Grained Classification Task.

Philip T. G. Jackson, Stephen Bonner, Ning Jia, Christopher J. Holder, Jonathan Stonehouse, Boguslaw Obara

Proceedings of the International Joint Conference on Neural Networks, 2021

Rank over Class: The Untapped Potential of Ranking in Natural Language Processing.

Amir Atapour-Abarghouei, Stephen Bonner, Andrew Stephen McGough

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Advances in learning and understanding with graphs through machine learning.

Stephen Bonner

PhD thesis, 2020

BLOB: A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals.

Otmane Sakhi, Stephen Bonner, David Rohde, Flavian Vasile

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Leveraging Synthetic Subject Invariant EEG Signals for Zero Calibration BCI.

Nik Khadijah Nik Aznan, Amir Atapour Abarghouei, Stephen Bonner, Jason D. Connolly, Toby P. Breckon

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Not Half Bad: Exploring Half-Precision in Graph Convolutional Neural Networks.

John Brennan, Stephen Bonner, Amir Atapour Abarghouei, Philip T. G. Jackson, Boguslaw Obara, Andrew Stephen McGough

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

Exploring the Semantic Content of Unsupervised Graph Embeddings: An Empirical Study.

Stephen Bonner, Ibad Kureshi, John Brennan, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara

Data Sci. Eng., 2019

Reconsidering Analytical Variational Bounds for Output Layers of Deep Networks.

Otmane Sakhi, Stephen Bonner, David Rohde, Flavian Vasile

CoRR, 2019

A Kings Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation.

Amir Atapour Abarghouei, Stephen Bonner, Andrew Stephen McGough

CoRR, 2019

Latent Variable Session-Based Recommendation.

David Rohde, Stephen Bonner

CoRR, 2019

Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification.

Nik Khadijah Nik Aznan, Amir Atapour Abarghouei, Stephen Bonner, Jason D. Connolly, Noura Al Moubayed, Toby P. Breckon

Proceedings of the International Joint Conference on Neural Networks, 2019

Causal Embeddings for Recommendation: An Extended Abstract.

Flavian Vasile, Stephen Bonner

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Coarse Annotation Refinement for Segmentation of Dot-Matrix Batchcodes.

Ning Jia, Christopher J. Holder, Stephen Bonner, Boguslaw Obara

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Style Augmentation: Data Augmentation via Style Randomization.

Philip T. G. Jackson, Amir Atapour Abarghouei, Stephen Bonner, Toby P. Breckon, Boguslaw Obara

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Temporal Neighbourhood Aggregation: Predicting Future Links in Temporal Graphs via Recurrent Variational Graph Convolutions.

Stephen Bonner, Amir Atapour Abarghouei, Philip T. G. Jackson, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Volenti non fit injuria: Ransomware and its Victims.

Amir Atapour Abarghouei, Stephen Bonner, Andrew Stephen McGough

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

A King's Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation.

Amir Atapour Abarghouei, Stephen Bonner, Andrew Stephen McGough

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising.

David Rohde, Stephen Bonner, Travis Dunlop, Flavian Vasile, Alexandros Karatzoglou

CoRR, 2018

On the Classification of SSVEP-Based Dry-EEG Signals via Convolutional Neural Networks.

Nik Khadijah Nik Aznan, Stephen Bonner, Jason D. Connolly, Noura Al Moubayed, Toby P. Breckon

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018

Causal embeddings for recommendation.

Stephen Bonner, Flavian Vasile

Proceedings of the 12th ACM Conference on Recommender Systems, 2018

Using Machine Learning to reduce the energy wasted in Volunteer Computing Environments.

A. Stephen McGough, Matthew Forshaw, John Brennan, Noura Al Moubayed, Stephen Bonner

Proceedings of the Ninth International Green and Sustainable Computing Conference, 2018

Predicting the Computational Cost of Deep Learning Models.

Daniel Justus, John Brennan, Stephen Bonner, Andrew Stephen McGough

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

Temporal Graph Offset Reconstruction: Towards Temporally Robust Graph Representation Learning.

Stephen Bonner, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Evaluating the quality of graph embeddings via topological feature reconstruction.

Stephen Bonner, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016

GFP-X: A parallel approach to massive graph comparison using spark.

Stephen Bonner, John Brennan, Georgios Theodoropoulos, Ibad Kureshi, Andrew Stephen McGough

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

Deep topology classification: A new approach for massive graph classification.

Stephen Bonner, John Brennan, Georgios Theodoropoulos, Ibad Kureshi, Andrew Stephen McGough

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015

Data quality assessment and anomaly detection via map/reduce and linked data: A case study in the medical domain.

Stephen Bonner, Andrew Stephen McGough, Ibad Kureshi, John Brennan, Georgios Theodoropoulos, Laura Moss, David Corsar, Grigoris Antoniou

Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015