Efficient distributed simulation of a communication switch with bursty sources and losses. - Andrew Stephen McGough; Isi Mitrani (PADS, 2000)

Parallel simulation of ATM switches using relaxation. - Andrew Stephen McGough; Isi Mitrani (Perform. Evaluation, 2000)

Parallel simulations using recurrence relations and relaxation. - Andrew Stephen McGough (2000)

A Component Framework for HPC Applications. - Nathalie Furmento; Anthony Edward Mayer; A. Stephen McGough; Steven J. Newhouse; John Darlington (Euro-Par, 2001)

An Integrated Grid Environment for Component Applications. - Nathalie Furmento; Anthony Edward Mayer; A. Stephen McGough; Steven J. Newhouse; Tony Field; John Darlington (GRID, 2001)

Optimisation of component-based applications within a grid environment. - Nathalie Furmento; Anthony Edward Mayer; A. Stephen McGough; Steven J. Newhouse; Tony Field; John Darlington (SC, 2001)

Meaning and Behaviour in Grid Oriented Components. - Anthony Edward Mayer; A. Stephen McGough; Murtaza Gulamali; Laurie Robert Young; Jim Stanton; Steven J. Newhouse; John Darlington (GRID, 2002)

ICENI: Optimisation of component applications within a Grid environment. - Nathalie Furmento; Anthony Edward Mayer; A. Stephen McGough; Steven J. Newhouse; Tony Field; John Darlington (Parallel Comput., 2002)

Efficient parallel simulation of a sliding window protocol. - Andrew Stephen McGough; Isi Mitrani (Perform. Evaluation, 2002)

Making the Grid Predictable through Reservations and Performance Modelling. - Andrew Stephen McGough; Ali Afzal; John Darlington; Nathalie Furmento; Anthony Edward Mayer; Laurie Robert Young (Comput. J., 2005)

An End-to-end Workflow Pipeline for Large-scale Grid Computing. - Andrew Stephen McGough; Jeremy Cohen 002; John Darlington; Eleftheria Katsiri; William Lee 003; Sofia Panagiotidi; Yash Patel (J. Grid Comput., 2005)

Capacity Planning and Stochastic Scheduling in Large-Scale Grids. - Ali Afzal; John Darlington; Andrew Stephen McGough (e-Science, 2006)

Stochastic Workflow Scheduling with QoS Guarantees in Grid Computing Environments. - Ali Afzal; John Darlington; Andrew Stephen McGough (GCC, 2006)

QoS-Constrained Stochastic Workflow Scheduling in Enterprise and Scientific Grids. - Ali Afzal; John Darlington; Andrew Stephen McGough (GRID, 2006)

QoS Support For Workflows In A Volatile Grid. - Yash Patel; Andrew Stephen McGough; John Darlington (GRID, 2006)

Adding Instruments and Workflow Support to Existing Grid Architectures. - Dave Colling; Luke William Dickens; Tiziana Ferrari; Y. Hassoun; Constantinos Kotsokalis; Marko Krznaric; Janusz Martyniak; Andrew Stephen McGough; Elisabetta Ronchieri (International Conference on Computational Science (3), 2006)

Workflow Deployment in ICENI II. - Andrew Stephen McGough; William Lee 003; John Darlington (International Conference on Computational Science (3), 2006)

A Profitable Broker in a Volatile Utility Grid. - Yash Patel; Andrew Stephen McGough; John Darlington (Int. Trans. Syst. Sci. Appl., 2006)

ICENI. - A. Stephen McGough; William Lee 003; Jeremy Cohen 002; Eleftheria Katsiri; John Darlington (Workflows for e-Science, Scientific Workflows for Grids, 2007)

Enabling QoS for Service-Oriented Workflow on GRID. - Li Guo 002; Andrew Stephen McGough; Asif Akram; Dave Colling; Janusz Martyniak; Marko Krznaric (CIT, 2007)

GRIDCC: real-time workflow system. - Andrew Stephen McGough; Asif Akram; Li Guo 002; Marko Krznaric; Luke Dickens; Dave Colling; Janusz Martyniak; Roger S. Powell; Paul Kyberd; Constantinos Kotsokalis (WORKS@HPDC, 2007)

GRIDCC: A Real-time Grid workflow system with QoS. - Andrew Stephen McGough; Asif Akram; Li Guo 002; Marko Krznaric; Luke Dickens; Dave Colling; Janusz Martyniak; Roger S. Powell; Paul Kyberd; Chenxi Huang; Constantinos Kotsokalis; Panayotis Tsanakas (Sci. Program., 2007)

Adding Standards Based Job Submission to a Commodity Grid Broker. - Dave Colling; Andrew Stephen McGough; Jazz Mack Smith; Vesso Novov; Tiejun Ma; David Wallom; Xin Xiong (eScience, 2008)

Capacity planning and scheduling in Grid computing environments. - Ali Afzal; Andrew Stephen McGough; John Darlington (Future Gener. Comput. Syst., 2008)

A standards based approach to enabling legacy applications on the Grid. - Andrew Stephen McGough; William Lee 003; Shikta Das (Future Gener. Comput. Syst., 2008)

Intelligent Power Management Over Large Clusters. - Andrew Stephen McGough; Clive Gerrard; Paul Haldane; Dave Sharples; Daniel Swan; Paul Robinson; Sindre Hamlander; Stuart Wheater (GreenCom/CPSCom, 2010)

Analysis of Power-Saving Techniques over a Large Multi-use Cluster. - Andrew Stephen McGough; Clive Gerrard; Jonathan Noble; Paul Robinson; Stuart Wheater (DASC, 2011)

Developing a Cost-Effective Virtual Cluster on the Cloud. - Andrew Stephen McGough (GECON, 2011)

Reducing the Number of Miscreant Tasks Executions in a Multi-use Cluster. - Andrew Stephen McGough; Matthew Forshaw; Clive Gerrard; Stuart Wheater (CGC, 2012)

Massively parallel landscape-evolution modelling using general purpose graphical processing units. - A. Stephen McGough; S. Liang; M. Rapoportas; R. Grey; G. Kumar Vinod; D. Maddy; A. Trueman; John Wainwright (HiPC, 2012)

Analysis of power-saving techniques over a large multi-use cluster with variable workload. - Andrew Stephen McGough; Matthew Forshaw; Clive Gerrard; Paul Robinson; Stuart Wheater (Concurr. Comput. Pract. Exp., 2013)

Flood modelling for cities using Cloud computing. - Vassilis Glenis; Andrew Stephen McGough; Vedrana Kutija; Chris G. Kilsby; Simon Woodman (J. Cloud Comput., 2013)

Trace-Driven Simulation for Energy Consumption in High Throughput Computing Systems. - Matthew Forshaw; Nigel Thomas; A. Stephen McGough (DS-RT, 2014)

Optimal Hiring of Cloud Servers. - Andrew Stephen McGough; Isi Mitrani (EPEW, 2014)

Energy-efficient Checkpointing in High-throughput Cycle-stealing Distributed Systems. - Matthew Forshaw; Andrew Stephen McGough; Nigel Thomas (PASM, 2014)

Comparison of a cost-effective virtual cloud cluster with an existing campus cluster. - Andrew Stephen McGough; Matthew Forshaw; Clive Gerrard; Stuart Wheater; Ben Allen; Paul Robinson (Future Gener. Comput. Syst., 2014)

Reduction of wasted energy in a volunteer computing system through Reinforcement Learning. - A. Stephen McGough; Matthew Forshaw (Sustain. Comput. Informatics Syst., 2014)

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 001; Laura Moss; David Corsar; Grigoris Antoniou (IEEE BigData, 2015)

Insider Threats: Identifying Anomalous Human Behaviour in Heterogeneous Systems Using Beneficial Intelligent Software (Ben-ware). - Andrew Stephen McGough; David Wall; John Brennan; Georgios Theodoropoulos 001; Ed Ruck-Keene; Budi Arief; Carl Gamble; John S. Fitzgerald; Aad P. A. van Moorsel; Sujeewa Alwis (MIST@CCS, 2015)

Energy-Aware Simulation of Workflow Execution in High Throughput Computing Systems. - A. Stephen McGough; Matthew Forshaw (DS-RT, 2015)

Flipping the priority: effects of prioritising HTC jobs on energy consumption in a multi-use cluster. - Matthew Forshaw; A. Stephen McGough (SimuTools, 2015)

Ben-ware: Identifying Anomalous Human Behaviour in Heterogeneous Systems Using Beneficial Intelligent Software. - Andrew Stephen McGough; Budi Arief; Carl Gamble; David Wall; John Brennan; John S. Fitzgerald; Aad P. A. van Moorsel; Sujeewa Alwis; Georgios Theodoropoulos 001; Ed Ruck-Keene (J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl., 2015)

Deep topology classification: A new approach for massive graph classification. - Stephen Bonner; John Brennan; Georgios Theodoropoulos 001; Ibad Kureshi; Andrew Stephen McGough (IEEE BigData, 2016)

GFP-X: A parallel approach to massive graph comparison using spark. - Stephen Bonner; John Brennan; Georgios Theodoropoulos 001; Ibad Kureshi; Andrew Stephen McGough (IEEE BigData, 2016)

SMS Spam Filtering Using Probabilistic Topic Modelling and Stacked Denoising Autoencoder. - Noura Al Moubayed; Toby P. Breckon; Peter Matthews; A. Stephen McGough (ICANN (2), 2016)

HTC-Sim: a trace-driven simulation framework for energy consumption in high-throughput computing systems. - Matthew Forshaw; A. Stephen McGough; Nigel Thomas (Concurr. Comput. Pract. Exp., 2016)

Evaluating the quality of graph embeddings via topological feature reconstruction. - Stephen Bonner; John Brennan; Ibad Kureshi; Georgios Theodoropoulos 001; Andrew Stephen McGough; Boguslaw Obara (IEEE BigData, 2017)

Identifying Changes in the Cybersecurity Threat Landscape Using the LDA-Web Topic Modelling Data Search Engine. - Noura Al Moubayed; David Wall; A. Stephen McGough (HCI (22), 2017)

Enhanced detection of movement onset in EEG through deep oversampling. - Noura Al Moubayed; Bashar Awwad Shiekh Hasan; Andrew Stephen McGough (IJCNN, 2017)

Using Machine Learning in Trace-driven Energy-Aware Simulations of High-Throughput Computing Systems. - A. Stephen McGough; Noura Al Moubayed; Matthew Forshaw (ICPE Companion, 2017)

Temporal Graph Offset Reconstruction: Towards Temporally Robust Graph Representation Learning. - Stephen Bonner; John Brennan; Ibad Kureshi; Georgios Theodoropoulos 001; Andrew Stephen McGough; Boguslaw Obara (IEEE BigData, 2018)

CAM: A Combined Attention Model for Natural Language Inference. - Amit Gajbhiye; Sardar F. Jaf; Noura Al Moubayed; Steven Bradley; A. Stephen McGough (IEEE BigData, 2018)

Predicting the Computational Cost of Deep Learning Models. - Daniel Justus; John Brennan; Stephen Bonner; Andrew Stephen McGough (IEEE BigData, 2018)

TMIXT: A process flow for Transcribing MIXed handwritten and machine-printed Text. - Fady Medhat; Mahnaz Mohammadi; Sardar F. Jaf; Chris G. Willcocks; Toby P. Breckon; Peter Matthews; Andrew Stephen McGough; Georgios Theodoropoulos 001; Boguslaw Obara (IEEE BigData, 2018)

Simulation of Virtual Machine Live Migration in High Throughput Computing Environments. - Osama Nasser Alrajeh; Matthew Forshaw; Andrew Stephen McGough; Nigel Thomas (DS-RT, 2018)

Segmenting Residential Smart Meter Data for Short-Term Load Forecasting. - Alexander J. M. Kell; A. Stephen McGough; Matthew Forshaw (e-Energy, 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 (IGSC, 2018)

Type-2 Diabetes Mellitus Diagnosis from Time Series Clinical Data Using Deep Learning Models. - Zakhriya Alhassan; A. Stephen McGough; Riyad Alshammari; Tahani Daghstani; David Budgen; Noura Al Moubayed (ICANN (3), 2018)

An Exploration of Dropout with RNNs for Natural Language Inference. - Amit Gajbhiye; Sardar F. Jaf; Noura Al Moubayed; A. Stephen McGough; Steven Bradley (ICANN (3), 2018)

Black-Box Variational Inference for Stochastic Differential Equations. - Thomas Ryder; Andrew Golightly; A. Stephen McGough; Dennis Prangle (ICML, 2018)

Stacked Denoising Autoencoders for Mortality Risk Prediction Using Imbalanced Clinical Data. - Zakhriya Alhassan; David Budgen; Riyad Alshammari; Tahani Daghstani; A. Stephen McGough; Noura Al Moubayed (ICMLA, 2018)

Evaluation of Energy Consumption of Replicated Tasks in a Volunteer Computing Environment. - A. Stephen McGough; Matthew Forshaw (ICPE Companion, 2018)

Black-Box Autoregressive Density Estimation for State-Space Models. - Tom Ryder; Andrew Golightly; A. Stephen McGough; Dennis Prangle (CoRR, 2018)

Introduction to special issue on Energy-Aware Simulation and Modelling (ENERGY-SIM). - A. Stephen McGough; Matthew Forshaw (Sustain. Comput. Informatics Syst., 2018)

On the Use of Neural Text Generation for the Task of Optical Character Recognition. - Mahnaz Mohammadi; Sardar F. Jaf; Andrew Stephen McGough; Toby P. Breckon; Peter Matthews; Georgios Theodoropoulos 001; Boguslaw Obara (AICCSA, 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 (IEEE BigData, 2019)

Volenti non fit injuria: Ransomware and its Victims. - Amir Atapour Abarghouei; Stephen Bonner; Andrew Stephen McGough (IEEE BigData, 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 001; Andrew Stephen McGough; Boguslaw Obara (IEEE BigData, 2019)

Modelling Carbon Tax in the UK Electricity Market using an Agent-Based Model. - Alexander J. M. Kell; Matthew Forshaw; A. Stephen McGough (e-Energy, 2019)

ElecSim: Monte-Carlo Open-Source Agent-Based Model to Inform Policy for Long-Term Electricity Planning. - Alexander J. M. Kell; Matthew Forshaw; A. Stephen McGough (e-Energy, 2019)

Optimising energy and overhead for large parameter space simulations. - Alexander J. M. Kell; Matthew Forshaw; A. Stephen McGough (IGSC, 2019)

The Northumberland Dolphin Dataset: A Multimedia Individual Cetacean Dataset for Fine-Grained Categorisation. - Cameron Trotter; Georgia Atkinson; Matthew Sharpe; A. Stephen McGough; Nick Wright; Per Berggren (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)

Exploring the Semantic Content of Unsupervised Graph Embeddings: An Empirical Study. - Stephen Bonner; Ibad Kureshi; John Brennan; Georgios Theodoropoulos 001; Andrew Stephen McGough; Boguslaw Obara (Data Sci. Eng., 2019)

NUFEB: A massively parallel simulator for individual-based modelling of microbial communities. - Bowen Li 005; Denis Taniguchi; Pahala Gedara Jayathilake; Valentina Gogulancea; Rebeca Gonzalez-Cabaleiro; Jinju Chen; Andrew Stephen McGough; Irina Dana Ofiteru; Thomas P. Curtis; Paolo Zuliani (PLoS Comput. Biol., 2019)

Resolving the cybersecurity Data Sharing Paradox to scale up cybersecurity via a co-production approach towards data sharing. - Amir Atapour Abarghouei; A. Stephen McGough; David S. Wall (IEEE BigData, 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 (IEEE BigData, 2020)

Exploring market power using deep reinforcement learning for intelligent bidding strategies. - Alexander J. M. Kell; Matthew Forshaw; A. Stephen McGough (IEEE BigData, 2020)

Long-term electricity market agent based model validation using genetic algorithm based optimization. - Alexander J. M. Kell; Matthew Forshaw; A. Stephen McGough (e-Energy, 2020)

Optimizing carbon tax for decentralized electricity markets using an agent-based model. - Alexander J. M. Kell; A. Stephen McGough; Matthew Forshaw (e-Energy, 2020)

Distributed Disk Store. - Mohammad Samawat Ullah; A. Stephen McGough (ICCA, 2020)

NDD20: A large-scale few-shot dolphin dataset for coarse and fine-grained categorisation. - Cameron Trotter; Georgia Atkinson; Matthew Sharpe; Kirsten Richardson; A. Stephen McGough; Nick Wright; Ben Burville; Per Berggren (CoRR, 2020)

Bonsai-Net: One-Shot Neural Architecture Search via Differentiable Pruners. - Rob Geada; Dennis Prangle; Andrew Stephen McGough (CoRR, 2020)

Beyond the topics: how deep learning can improve the discriminability of probabilistic topic modelling. - Noura Al Moubayed; Andrew Stephen McGough; Bashar Awwad Shiekh Hasan (PeerJ Comput. Sci., 2020)

Rank over Class: The Untapped Potential of Ranking in Natural Language Processing. - Amir Atapour-Abarghouei; Stephen Bonner; Andrew Stephen McGough (IEEE BigData, 2021)

Application of deep learning to camera trap data for ecologists in planning / engineering - Can captivity imagery train a model which generalises to the wild? - Ryan Curry; Cameron Trotter; A. Stephen McGough (IEEE BigData, 2021)

Using the One Minute Paper to Gain Insight into Potential Threshold Concepts in Artificial Intelligence Courses. - Becky Allen; Marie Devlin; A. Stephen McGough (CEP, 2021)

The impact of online machine-learning methods on long-term investment decisions and generator utilization in electricity markets. - Alexander J. M. Kell; A. Stephen McGough; Matthew Forshaw (Sustain. Comput. Informatics Syst., 2021)

Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets. - Michael Luke Battle; Amir Atapour-Abarghouei; Andrew Stephen McGough (IEEE Big Data, 2022)

Optimizing a domestic battery and solar photovoltaic system with deep reinforcement learning. - Alexander J. M. Kell; A. Stephen McGough; Matthew Forshaw (IEEE Big Data, 2022)

A systematic literature review on machine learning for electricity market agent-based models. - Alexander J. M. Kell; A. Stephen McGough; Matthew Forshaw (IEEE Big Data, 2022)

Explainable Deep Learning to Profile Mitochondrial Disease Using High Dimensional Protein Expression Data. - Atif Khan 003; Conor Lawless; Amy E. Vincent; Satish Pilla; Sushanth Ramesh; A. Stephen McGough (IEEE Big Data, 2022)

Towards Automatic Cetacean Photo-Identification: A Framework for Fine-Grain, Few-Shot Learning in Marine Ecology. - Cameron Trotter; Nick Wright; A. Stephen McGough; Matthew Sharpe; Barbara Cheney; Mònica Arso Civil; Reny Tyson Moore; Jason Allen; Per Berggren (IEEE Big Data, 2022)

SpiderNet: Hybrid Differentiable-Evolutionary Architecture Search via Train-Free Metrics. - Rob Geada; Andrew Stephen McGough (CVPR Workshops, 2022)

Analysis of Reinforcement Learning for Determining Task Replication in Workflows. - Andrew Stephen McGough; Matthew Forshaw (EPEW, 2022)

Machine learning applications for electricity market agent-based models: A systematic literature review. - Alexander J. M. Kell; A. Stephen McGough; Matthew Forshaw (CoRR, 2022)

Long-term Reproducibility for Neural Architecture Search. - David Towers; Matthew Forshaw; Amir Atapour-Abarghouei; Andrew Stephen McGough (CoRR, 2022)

Machine Learning, Deep Learning and Statistical Analysis for forecasting building energy consumption - A systematic review. - Mohamad Khalil; A. Stephen McGough; Zoya Pourmirza; Mehdi Pazhoohesh; Sara Walker (Eng. Appl. Artif. Intell., 2022)

PeaGlyph: Glyph design for investigation of balanced data structures. - Kenan Koc; Andrew Stephen McGough; Sara Johansson Fernstad (Inf. Vis., 2022)

Toward a Framework for Teaching Artificial Intelligence to a Higher Education Audience. - Becky Allen; Andrew Stephen McGough; Marie Devlin (ACM Trans. Comput. Educ., 2022)

FEGR: Feature Enhanced Graph Representation Method for Graph Classification. - Mohamad Elhadi Abushofa; Amir Atapour Abarghouei; Matthew Forshaw; Andrew Stephen McGough (ASONAM, 2023)

How much data do I need? A case study on medical data. - Ayse Betul Cengiz; A. Stephen McGough (IEEE Big Data, 2023)

The Forecastability of Underlying Building Electricity Demand from Time Series Data. - Mohamad Khalil; A. Stephen McGough; Hussain Kazmi; Sara Walker (IEEE Big Data, 2023)

NCL-SM: A Fully Annotated Dataset of Images from Human Skeletal Muscle Biopsies. - Atif Khan 003; Conor Lawless; Amy E. Vincent; Charlotte Warren; Valeria Di Leo; Tiago Gomes; A. Stephen McGough (IEEE Big Data, 2023)

SWiMM DEEPeR: A Simulated Underwater Environment for Tracking Marine Mammals Using Deep Reinforcement Learning and BlueROV2. - Samuel Appleby; Kirsten Crane; Giacomo Bergami; A. Stephen McGough (CoG, 2023)

Hand Guided High Resolution Feature Enhancement for Fine-Grained Atomic Action Segmentation within Complex Human Assemblies. - Matthew Kent Myers; Nick Wright; A. Stephen McGough; Nicholas G. Martin (WACV (Workshops), 2023)

Predicting the Performance of a Computing System with Deep Networks. - Mehmet Cengiz; Matthew Forshaw; Amir Atapour-Abarghouei; Andrew Stephen McGough (ICPE, 2023)

Introducing NCL-SM: A Fully Annotated Dataset of Images from Human Skeletal Muscle Biopsies. - Atif Khan 003; Conor Lawless; Amy E. Vincent; Charlotte Warren; Valeria Di Leo; Tiago Gomes; A. Stephen McGough (CoRR, 2023)

The Effects of Signal-to-Noise Ratio on Generative Adversarial Networks Applied to Marine Bioacoustic Data. - Georgia Atkinson; Nick Wright; A. Stephen McGough; Per Berggren (CoRR, 2023)

Evaluating Deep Graph Network Performance by Augmenting Node Features with Structural Features. - Mohamad Elhadi Abushofa; Amir Atapour-Abarghouei; Matthew Forshaw; A. Stephen McGough (ASONAM (3), 2024)

Insights from the Use of Previously Unseen Neural Architecture Search Datasets. - Rob Geada; David Towers; Matthew Forshaw; Amir Atapour-Abarghouei; A. Stephen McGough (CVPR, 2024)

O-TALC: Steps Towards Combating Oversegmentation within Online Action Segmentation. - Matthew Kent Myers; Nick Wright; A. Stephen McGough; Nicholas G. Martin (CoRR, 2024)

My Emotion on your face: The use of Facial Keypoint Detection to preserve Emotions in Latent Space Editing. - Jingrui He; Andrew Stephen McGough (CoRR, 2025)