Stephen Bonner

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Efficient comparison of massive graphs through the use of 'graph fingerprints'.

G. Theodoropoulos, A. McGough, Stephen Bonner, 2016, MLG 2016.

Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery

William L. Hamilton, I. Barrett, O. Engkvist, 2021, Artificial Intelligence in the Life Sciences.

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

A. Bender, I. Barrett, O. Engkvist, 2021, Briefings Bioinform..

Implications of Topological Imbalance for Representation Learning on Biomedical Knowledge Graphs

Jian Tang, I. Barrett, O. Engkvist, 2021, Briefings Bioinform..

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

I. Barrett, Stephen Bonner, Cheng Ye, 2021, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Predicting Potential Drug Targets Using Tensor Factorisation and Knowledge Graph Embeddings

I. Barrett, Stephen Bonner, Cheng Ye, 2021, ArXiv.

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

Andreas Bender, Ola Engkvist, Stephen Bonner, 2021, Briefings in bioinformatics.

Neuronal Graphs: A Graph Theory Primer for Microscopic, Functional Networks of Neurons Recorded by Calcium Imaging

Stephen Bonner, Carl J. Nelson, Stephen Bonner, 2020, Frontiers in Neural Circuits.

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

Andriy Nikolov, Stephen Bonner, Benedek Rozemberczki, 2021, IJCAI.

A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Synergy, and Drug-Drug Interaction Prediction

A. Nikolov, M. Ughetto, Eliseo Papa, 2021 .

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

A. Stephen McGough, Stephen Bonner, Amir Atapour Abarghouei, 2019, 2019 IEEE International Conference on Big Data (Big Data).

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

Toby P. Breckon, Stephen Bonner, Nik Khadijah Nik Aznan, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

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

Alexandros Karatzoglou, Stephen Bonner, David Rohde, 2018, ArXiv.

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

Toby P. Breckon, Stephen Bonner, Nik Khadijah Nik Aznan, 2018, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Style Augmentation: Data Augmentation via Style Randomization

Toby P. Breckon, Philip T. G. Jackson, Boguslaw Obara, 2018, CVPR Workshops.

Causal embeddings for recommendation

Stephen Bonner, Flavian Vasile, Flavian Vasile, 2017, RecSys.

Predicting the Computational Cost of Deep Learning Models

A. Stephen McGough, John Brennan, Stephen Bonner, 2018, 2018 IEEE International Conference on Big Data (Big Data).

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

Philip T. G. Jackson, A. McGough, B. Obara, 2019, 2019 IEEE International Conference on Big Data (Big Data).

Exploring the Evolution of Big Data Technologies

John Brennan, Ibad Kureshi, Stephen Bonner, 2017 .

Coarse Annotation Refinement for Segmentation of Dot-Matrix Batchcodes

Boguslaw Obara, Ning Jia, Christopher J. Holder, 2019, 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA).

Evaluating the quality of graph embeddings via topological feature reconstruction

A. Stephen McGough, John Brennan, Ibad Kureshi, 2017, 2017 IEEE International Conference on Big Data (Big Data).

Temporal Graph Offset Reconstruction: Towards Temporally Robust Graph Representation Learning

A. Stephen McGough, John Brennan, Ibad Kureshi, 2018, 2018 IEEE International Conference on Big Data (Big Data).

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

A. Stephen McGough, Stephen Bonner, Amir Atapour Abarghouei, 2020, 2021 IEEE International Conference on Big Data (Big Data).

Camera Bias in a Fine Grained Classification Task pdf

Philip T. G. Jackson, Boguslaw Obara, Stephen Bonner, 2020, 2021 International Joint Conference on Neural Networks (IJCNN).

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

Flavian Vasile, Otmane Sakhi, David Rohde, 2020, KDD.

Deep topology classification: A new approach for massive graph classification

A. Stephen McGough, John Brennan, Ibad Kureshi, 2016, 2016 IEEE International Conference on Big Data (Big Data).

Using Hadoop To Implement a Semantic Method Of Assessing The Quality Of Research Medical Datasets

Ibad Kureshi, Grigoris Antoniou, Stephen Bonner, 2014, BigDataScience '14.

Reconsidering Analytical Variational Bounds for Output Layers of Deep Networks pdf

Stephen Bonner, David Rohde, Flavian Vasile, 2019, ArXiv.

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

A. Stephen McGough, Philip T. G. Jackson, Boguslaw Obara, 2020, 2020 IEEE International Conference on Big Data (Big Data).

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

A. Stephen McGough, John Brennan, Ibad Kureshi, 2018, Data Science and Engineering.

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

A. Stephen McGough, John Brennan, Stephen Bonner, 2018, 2018 Ninth International Green and Sustainable Computing Conference (IGSC).