Stephen Bonner

Publication Activity (10 Years)

Years Active: 2015-2022
Publications (10 Years): 49

Top Topics

Machine Learning

Top Venues

Briefings Bioinform.

Publications

Benedek Rozemberczki, Stephen Bonner, Andriy Nikolov, Michaël Ughetto, Sebastian Nilsson, Eliseo Papa
A Unified View of Relational Deep Learning for Drug Pair Scoring. IJCAI (2022)
Stephen Bonner, Ufuk Kirik, Ola Engkvist, Jian Tang, Ian P. Barrett
Implications of topological imbalance for representation learning on biomedical knowledge graphs. Briefings Bioinform. 23 (5) (2022)
Cheng Ye, Rowan Swiers, Stephen Bonner, Ian P. Barrett
A Knowledge Graph-Enhanced Tensor Factorisation Model for Discovering Drug Targets. IEEE ACM Trans. Comput. Biol. Bioinform. 19 (6) (2022)
Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, Andreas Bender, Charles Tapley Hoyt, William L. Hamilton
A review of biomedical datasets relating to drug discovery: a knowledge graph perspective. Briefings Bioinform. 23 (6) (2022)
Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, William L. Hamilton
Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery. CoRR (2021)
Philip T. G. Jackson, Stephen Bonner, Ning Jia, Christopher J. Holder, Jon Stonehouse, Boguslaw Obara
Camera Bias in a Fine Grained Classification Task. IJCNN (2021)
Cheng Ye, Rowan Swiers, Stephen Bonner, Ian P. Barrett
Predicting Potential Drug Targets Using Tensor Factorisation and Knowledge Graph Embeddings. CoRR (2021)
Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, Andreas Bender, William L. Hamilton
A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective. CoRR (2021)
Amir Atapour-Abarghouei, Stephen Bonner, Andrew Stephen McGough
Rank over Class: The Untapped Potential of Ranking in Natural Language Processing. IEEE BigData (2021)
Stephen Bonner, Ufuk Kirik, Ola Engkvist, Jian Tang, Ian P. Barrett
Implications of Topological Imbalance for Representation Learning on Biomedical Knowledge Graphs. CoRR (2021)
Benedek Rozemberczki, Stephen Bonner, Andriy Nikolov, Michaël Ughetto, Sebastian Nilsson, Eliseo Papa
A Unified View of Relational Deep Learning for Drug Pair Scoring. CoRR (2021)
Amir Atapour Abarghouei, Stephen Bonner, Andrew Stephen McGough
Rank over Class: The Untapped Potential of Ranking in Natural Language Processing. CoRR (2020)
Otmane Sakhi, Stephen Bonner, David Rohde, Flavian Vasile
BLOB : A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals. CoRR (2020)
John Brennan, Stephen Bonner, Amir Atapour Abarghouei, Philip T. G. Jackson, Boguslaw Obara, Andrew Stephen McGough
Not Half Bad: Exploring Half-Precision in Graph Convolutional Neural Networks. IEEE BigData (2020)
Nik Khadijah Nik Aznan, Amir Atapour Abarghouei, Stephen Bonner, Jason D. Connolly, Toby P. Breckon
Leveraging Synthetic Subject Invariant EEG Signals for Zero Calibration BCI. ICPR (2020)
Otmane Sakhi, Stephen Bonner, David Rohde, Flavian Vasile
BLOB: A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals. KDD (2020)
John Brennan, Stephen Bonner, Amir Atapour Abarghouei, Philip T. G. Jackson, Boguslaw Obara, Andrew Stephen McGough
Not Half Bad: Exploring Half-Precision in Graph Convolutional Neural Networks. CoRR (2020)
Philip T. G. Jackson, Stephen Bonner, Ning Jia, Christopher J. Holder, Jon Stonehouse, Boguslaw Obara
Camera Bias in a Fine Grained Classification Task. CoRR (2020)
Amir Atapour Abarghouei, Stephen Bonner, Andrew Stephen McGough
A Kings Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation. CoRR (2019)
Stephen Bonner, Amir Atapour Abarghouei, Philip T. G. Jackson, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Temporal Neighbourhood Aggregation: Predicting Future Links in Temporal Graphs via Recurrent Variational Graph Convolutions. IEEE BigData (2019)
Flavian Vasile, Stephen Bonner
Causal Embeddings for Recommendation: An Extended Abstract. IJCAI (2019)
Stephen Bonner, Ibad Kureshi, John Brennan, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Exploring the Semantic Content of Unsupervised Graph Embeddings: An Empirical Study. Data Sci. Eng. 4 (3) (2019)
Otmane Sakhi, Stephen Bonner, David Rohde, Flavian Vasile
Reconsidering Analytical Variational Bounds for Output Layers of Deep Networks. CoRR (2019)
David Rohde, Stephen Bonner
Latent Variable Session-Based Recommendation. CoRR (2019)
Stephen Bonner, Flavian Vasile
Causal Embeddings for Recommendation: An Extended Abstract. CoRR (2019)
Philip T. G. Jackson, Amir Atapour Abarghouei, Stephen Bonner, Toby P. Breckon, Boguslaw Obara
Style Augmentation: Data Augmentation via Style Randomization. CVPR Workshops (2019)
Stephen Bonner, Amir Atapour Abarghouei, Philip T. G. Jackson, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Temporal Neighbourhood Aggregation: Predicting Future Links in Temporal Graphs via Recurrent Variational Graph Convolutions. CoRR (2019)
Amir Atapour Abarghouei, Stephen Bonner, Andrew Stephen McGough
Volenti non fit injuria: Ransomware and its Victims. IEEE BigData (2019)
Amir Atapour Abarghouei, Stephen Bonner, Andrew Stephen McGough
Volenti non fit injuria: Ransomware and its Victims. CoRR (2019)
Amir Atapour Abarghouei, Stephen Bonner, Andrew Stephen McGough
A King's Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation. IEEE BigData (2019)
Nik Khadijah Nik Aznan, Amir Atapour Abarghouei, Stephen Bonner, Jason D. Connolly, Noura Al Moubayed, Toby P. Breckon
Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification. IJCNN (2019)
Ning Jia, Christopher J. Holder, Stephen Bonner, Boguslaw Obara
Coarse Annotation Refinement for Segmentation of Dot-Matrix Batchcodes. ICMLA (2019)
A. Stephen McGough, Matthew Forshaw, John Brennan, Noura Al Moubayed, Stephen Bonner
Using Machine Learning to reduce the energy wasted in Volunteer Computing Environments. CoRR (2018)
Daniel Justus, John Brennan, Stephen Bonner, Andrew Stephen McGough
Predicting the Computational Cost of Deep Learning Models. IEEE BigData (2018)
Stephen Bonner, Flavian Vasile
Causal embeddings for recommendation. RecSys (2018)
A. Stephen McGough, Matthew Forshaw, John Brennan, Noura Al Moubayed, Stephen Bonner
Using Machine Learning to reduce the energy wasted in Volunteer Computing Environments. IGSC (2018)
Philip T. G. Jackson, Amir Atapour Abarghouei, Stephen Bonner, Toby P. Breckon, Boguslaw Obara
Style Augmentation: Data Augmentation via Style Randomization. CoRR (2018)
Stephen Bonner, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Temporal Graph Offset Reconstruction: Towards Temporally Robust Graph Representation Learning. CoRR (2018)
Daniel Justus, John Brennan, Stephen Bonner, Andrew Stephen McGough
Predicting the Computational Cost of Deep Learning Models. CoRR (2018)
David Rohde, Stephen Bonner, Travis Dunlop, Flavian Vasile, Alexandros Karatzoglou
RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising. CoRR (2018)
Nik Khadijah Nik Aznan, Stephen Bonner, Jason D. Connolly, Noura Al Moubayed, Toby P. Breckon
On the Classification of SSVEP-Based Dry-EEG Signals via Convolutional Neural Networks. CoRR (2018)
Stephen Bonner, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Temporal Graph Offset Reconstruction: Towards Temporally Robust Graph Representation Learning. IEEE BigData (2018)
Nik Khadijah Nik Aznan, Stephen Bonner, Jason D. Connolly, Noura Al Moubayed, Toby P. Breckon
On the Classification of SSVEP-Based Dry-EEG Signals via Convolutional Neural Networks. SMC (2018)
Stephen Bonner, Ibad Kureshi, John Brennan, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Exploring the Semantic Content of Unsupervised Graph Embeddings: An Empirical Study. CoRR (2018)
Stephen Bonner, John Brennan, Ibad Kureshi, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Evaluating the quality of graph embeddings via topological feature reconstruction. IEEE BigData (2017)
Stephen Bonner, Flavian Vasile
Causal Embeddings for Recommendation. CoRR (2017)
Stephen Bonner, John Brennan, Georgios Theodoropoulos, Ibad Kureshi, Andrew Stephen McGough
GFP-X: A parallel approach to massive graph comparison using spark. IEEE BigData (2016)
Stephen Bonner, John Brennan, Georgios Theodoropoulos, Ibad Kureshi, Andrew Stephen McGough
Deep topology classification: A new approach for massive graph classification. IEEE BigData (2016)
Stephen Bonner, Andrew Stephen McGough, Ibad Kureshi, John Brennan, Georgios Theodoropoulos, Laura Moss, David Corsar, Grigoris Antoniou
Data quality assessment and anomaly detection via map/reduce and linked data: A case study in the medical domain. IEEE BigData (2015)