The u-SIG System; A Connectionist Driven Simulation of Socially Interactive Agents. - Brian MacNamee; Padraig Cunningham (GAME-ON, 2002)

The problem of bias in training data in regression problems in medical decision support. - Brian MacNamee; Padraig Cunningham; Stephen Byrne; O. I. Corrigan (Artif. Intell. Medicine, 2002)

Simulating Virtual Humans Across Diverse Situations. - Brian MacNamee; Simon Dobbyn; Padraig Cunningham; Carol O'Sullivan (IVA, 2003)

Smart Objects for Attentive Agents. - Christopher Peters 001; Simon Dobbyn; Brian MacNamee; Carol O'Sullivan (WSCG, 2003)

Creating socially interactive no-player characters: The µ-SIV system. - Brian MacNamee; Padraig Cunningham (Int. J. Intell. Games Simul., 2003)

Back to the Future: Knowledge Light Case Base Cookery. - Qian Zhang; Rong Hu; Brian Mac Namee; Sarah Jane Delany (ECCBR Workshops, 2008)

Referring Expression Generation Challenge 2008 DIT System Descriptions (DIT-FBI, DIT-TVAS, DIT-CBSR, DIT-RBR, DIT-FBI-CBSR, DIT-TVAS-RBR). - John D. Kelleher; Brian Mac Namee (INLG, 2008)

Just Say It: An Evaluation of Speech Interfaces for Augmented Reality Design Applications. - Nicholas Hanlon; Brian Mac Namee; John D. Kelleher (AICS, 2009)

Learning without Default: A Study of One-Class Classification and the Low-Default Portfolio Problem. - Kenneth Kennedy; Brian Mac Namee; Sarah Jane Delany (AICS, 2009)

Forked! A demonstration of physics realism in augmented reality. - David Beaney; Brian Mac Namee (ISMAR, 2009)

Widening the Evaluation Net. - Brian Mac Namee; Mark Dunne (IVA, 2009)

Cross-Disciplinary Approaches for Developing Serious Games in Higher Education. - Pauline Rooney; K. C. O'Rourke; Greg Burke; Brian MacNamee; Claudia Igbrude (VS-GAMES, 2009)

Computer Graphics and Games, Agent Based Modeling in. - Brian Mac Namee (Encyclopedia of Complexity and Systems Science, 2009)

Situating Spatial Templates for Human-Robot Interaction. - John D. Kelleher; Robert J. Ross; Brian Mac Namee; Colm Sloan (AAAI Fall Symposium: Dialog with Robots, 2010)

Visual Salience and Reference Resolution in Situated Dialogues: A Corpus-based Evaluation. - Niels Schuette; John D. Kelleher; Brian Mac Namee (AAAI Fall Symposium: Dialog with Robots, 2010)

Off to a Good Start: Using Clustering to Select the Initial Training Set in Active Learning. - Rong Hu; Brian Mac Namee; Sarah Jane Delany (FLAIRS, 2010)

Handling Concept Drift in a Text Data Stream Constrained by High Labelling Cost. - Patrick Lindstrom; Sarah Jane Delany; Brian Mac Namee (FLAIRS, 2010)

EGAL: Exploration Guided Active Learning for TCBR. - Rong Hu; Sarah Jane Delany; Brian Mac Namee (ICCBR, 2010)

CBTV: Visualising Case Bases for Similarity Measure Design and Selection. - Brian Mac Namee; Sarah Jane Delany (ICCBR, 2010)

Motion in Augmented Reality Games: An Engine for Creating Plausible Physical Interactions in Augmented Reality Games. - Brian Mac Namee; David Beaney; Qingqing Dong (Int. J. Comput. Games Technol., 2010)

Feasibility study of utility-directed behaviour for computer game agents. - Colm Sloan; John D. Kelleher; Brian Mac Namee (Advances in Computer Entertainment Technology, 2011)

Feeling the ambiance: using smart ambiance to increase contextual awareness in game agents. - Colm Sloan; John D. Kelleher; Brian Mac Namee (FDG, 2011)

The effect of occlusion on the semantics of projective spatial terms: a case study in grounding language in perception. - John D. Kelleher; Robert J. Ross; Colm Sloan; Brian Mac Namee (Cogn. Process., 2011)

Automatic Annotation of Referring Expressions in Situated Dialogues. - Niels Schütte; John D. Kelleher; Brian Mac Namee (Int. J. Comput. Linguistics Appl., 2011)

An Investigation Into Feature Selection for Oncological Survival Prediction. - Dmitry Strunkin; Brian Mac Namee; John D. Kelleher (ITNG, 2012)

The Turning, Stretching and Boxing Technique: A Step in the Right Direction. - Mark Dunne; Brian Mac Namee; John D. Kelleher (IVA, 2012)

Dynamic Estimation of Rater Reliability in Subjective Tasks Using Multi-armed Bandits. - Alexey Tarasov; Sarah Jane Delany; Brian Mac Namee (SocialCom/PASSAT, 2012)

Profiling instances in noise reduction. - Sarah Jane Delany; Nicola Segata; Brian Mac Namee (Knowl. Based Syst., 2012)

Expecting the Unexpected: Measure the Uncertainties for Mobile Robot Path Planning in Dynamic Environment. - Yan Li; Brian Mac Namee; John D. Kelleher (TAROS, 2013)

A window of opportunity: Assessing behavioural scoring. - Kenneth Kennedy; Brian Mac Namee; Sarah Jane Delany; M. O'Sullivan; N. Watson (Expert Syst. Appl., 2013)

Drift detection using uncertainty distribution divergence. - Patrick Lindstrom; Brian Mac Namee; Sarah Jane Delany (Evol. Syst., 2013)

Using semi-supervised classifiers for credit scoring. - Kenneth Kennedy; Brian Mac Namee; Sarah Jane Delany (J. Oper. Res. Soc., 2013)

The Effect of Sensor Errors in Situated Human-Computer Dialogue. - Niels Schütte; John D. Kelleher; Brian Mac Namee (VL@COLING, 2014)

NudgeAlong: A Case Based Approach to Changing User Behaviour. - Eoghan O'Shea; Sarah Jane Delany; Rob Lane; Brian Mac Namee (ICCBR, 2014)

Clarification Dialogues for Perception-based Errors in Situated Human-Computer Dialogues. - Niels Schütte; John D. Kelleher; Brian Mac Namee (MMRWHRI@ICMI, 2014)

Dynamic estimation of worker reliability in crowdsourcing for regression tasks: Making it work. - Alexey Tarasov; Sarah Jane Delany; Brian Mac Namee (Expert Syst. Appl., 2014)

Ensemble Topic Modeling via Matrix Factorization. - Mark Belford; Brian Mac Namee; Derek Greene (AICS, 2016)

An Open Data Driven Epidemiological Agent-Based Model for Irish Towns. - Elizabeth Hunter; Brian Mac Namee; John D. Kelleher (AICS, 2016)

Activist: A New Framework for Dataset Labelling. - Jack O'Neill; Sarah Jane Delany; Brian Mac Namee (AICS, 2016)

Benchmarking Multi-label Classification Algorithms. - Arjun Pakrashi; Derek Greene; Brian Mac Namee (AICS, 2016)

Model-Free and Model-Based Active Learning for Regression. - Jack O'Neill; Sarah Jane Delany; Brian Mac Namee (UKCI, 2016)

On Using Tree Visualisation Techniques to Support Source Code Comprehension. - Ivan Bacher; Brian Mac Namee; John D. Kelleher (VISSOFT, 2016)

Using Icicle Trees to Encode the Hierarchical Structure of Source Code. - Ivan Bacher; Brian Mac Namee; John D. Kelleher (EuroVis (Short Papers), 2016)

Active learning for text classification with reusability. - Rong Hu; Brian Mac Namee; Sarah Jane Delany (Expert Syst. Appl., 2016)

Graphical Perception of Value Distributions: An Evaluation of Non-Expert Viewers' Data Literacy. - Arkaitz Zubiaga; Brian Mac Namee (J. Community Informatics, 2016)

Synthetic Dataset Generation for Online Topic Modeling. - Mark Belford; Brian Mac Namee; Derek Greene (AICS, 2017)

Extending Jensen Shannon Divergence to Compare Multiple Corpora. - Jinghui Lu; Maeve Henchion; Brian Mac Namee (AICS, 2017)

Assessing the Usefulness of Different Feature Sets for Predicting the Comprehension Difficulty of Text. - Brian Mac Namee; John D. Kelleher; Noel Fitzpatrick (AICS, 2017)

The Code-Map Metaphor - A Review of Its Use Within Software Visualisations. - Ivan Bacher; Brian Mac Namee; John D. Kelleher (VISIGRAPP (3: IVAPP), 2017)

Stacked-MLkNN: A stacking based improvement to Multi-Label k-Nearest Neighbours. - Arjun Pakrashi; Brian Mac Namee (LIDTA@PKDD/ECML, 2017)

Rating by Ranking: An Improved Scale for Judgement-Based Labels. - Jack O'Neill; Sarah Jane Delany; Brian Mac Namee (IntRS@RecSys, 2017)

Scoped: Visualising the Scope Chain Within Source Code. - Ivan Bacher; Brian Mac Namee; John D. Kelleher (EuroVis (Short Papers), 2017)

Robot perception errors and human resolution strategies in situated human-robot dialogue. - Niels Schütte; Brian Mac Namee; John D. Kelleher (Adv. Robotics, 2017)

A Taxonomy for Agent-Based Models in Human Infectious Disease Epidemiology. - Elizabeth Hunter; Brian Mac Namee; John D. Kelleher (J. Artif. Soc. Soc. Simul., 2017)

Identifying Urban Canopy Coverage from Satellite Imagery Using Convolutional Neural Networks. - Niamh Donnelly; Conor Nugent; Brian Mac Namee (AICS, 2018)

A Comparison of Agent-Based Models and Equation Based Models for Infectious Disease Epidemiology. - Elizabeth Hunter; Brian Mac Namee; John D. Kelleher (AICS, 2018)

MeetupNet Dublin: Discovering Communities in Dublin's Meetup Network. - Arjun Pakrashi; Elham Abdullah Alghamdi; Brian Mac Namee; Derek Greene (AICS, 2018)

ROGER: An On-Line Flight Efficiency Monitoring System Using ADS-B Data. - Shen Wang 006; Aditya Grover; Brian Mac Namee; Philip Plantholt; Javier Lopez-Leones; Pablo Sanchez-Escalonilla (MDM, 2018)

Rank Scoring via Active Learning (RaScAL). - Jack O'Neill; Sarah Jane Delany; Brian Mac Namee (HumL@ISWC, 2018)

From Rankings to Ratings: Rank Scoring via Active Learning. - Jack O'Neill; Sarah Jane Delany; Brian Mac Namee (ISWC (Best Workshop Papers), 2018)

Scoped: Evaluating A Composite Visualisation of the Scope Chain Hierarchy Within Source Code. - Ivan Bacher; Brian Mac Namee; John D. Kelleher (VISSOFT, 2018)

The Code Mini-Map Visualisation: Encoding Conceptual Structures Within Source Code. - Ivan Bacher; Brian Mac Namee; John D. Kelleher (VISSOFT, 2018)

Kalman Filter-based Heuristic Ensemble: A New Perspective on Ensemble Classification Using Kalman Filters. - Arjun Pakrashi; Brian Mac Namee (CoRR, 2018)

Deep learning at the shallow end: Malware classification for non-domain experts. - Quan Le; Oisín Boydell; Brian Mac Namee; Mark Scanlon (Digit. Investig., 2018)

Stability of topic modeling via matrix factorization. - Mark Belford; Brian Mac Namee; Derek Greene (Expert Syst. Appl., 2018)

Using a Socioeconomic Segregation Burn-in Model to Initialise an Agent-Based Model for Infectious Diseases. - Elizabeth Hunter; Brian Mac Namee; John D. Kelleher (J. Artif. Soc. Soc. Simul., 2018)

A Topic-Based Approach to Multiple Corpus Comparison. - Jinghui Lu; Maeve Henchion; Brian Mac Namee (AICS, 2019)

On the Validity of Bayesian Neural Networks for Uncertainty Estimation. - John Mitros; Brian Mac Namee (AICS, 2019)

Anomaly Detection in Raw Audio Using Deep Autoregressive Networks. - Ellen Rushe; Brian Mac Namee (ICASSP, 2019)

The Elliptical Basis Function Data Descriptor (EBFDD) Network: A One-Class Classification Approach to Anomaly Detection. - Mehran Hossein Zadeh Bazargani; Brian Mac Namee (ECML/PKDD (1), 2019)

CascadeML: An Automatic Neural Network Architecture Evolution and Training Algorithm for Multi-label Classification (Best Technical Paper). - Arjun Pakrashi; Brian Mac Namee (SGAI Conf., 2019)

Are You in Pain? Predicting Pain and Stiffness from Wearable Sensor Activity Data. - Niladri Sett; Brian Mac Namee; Francesc Calvo; Brian Caulfield 001; John Costello; Seamas Donnelly; Jonas F. Dorn; Louis Jeay; Alison Keogh; Killian McManus; Ronan H. Mullan; Emer O'Hare; et al. (SGAI Conf., 2019)

A Categorisation of Post-hoc Explanations for Predictive Models. - John Mitros; Brian Mac Namee (CoRR, 2019)

CascadeML: An Automatic Neural Network Architecture Evolution and Training Algorithm for Multi-label Classification. - Arjun Pakrashi; Brian Mac Namee (CoRR, 2019)

KFHE-HOMER: Kalman Filter-based Heuristic Ensemble of HOMER for Multi-Label Classification. - Arjun Pakrashi; Brian Mac Namee (CoRR, 2019)

ZeLiC and ZeChipC: Time Series Interpolation Methods for Lebesgue or Event-based Sampling. - Matthieu Bellucci; Luis Miralles 001; Muhammad Atif Qureshi 001; Brian Mac Namee (CoRR, 2019)

Investigating the Effectiveness of Representations Based on Word-Embeddings in Active Learning for Labelling Text Datasets. - Jinghui Lu; Maeve Henchion; Brian Mac Namee (CoRR, 2019)

Real-time Bidding campaigns optimization using attribute selection. - Luis Miralles 001; Muhammad Atif Qureshi 001; Brian Mac Namee (CoRR, 2019)

Kalman Filter-based Heuristic Ensemble (KFHE): A new perspective on multi-class ensemble classification using Kalman filters. - Arjun Pakrashi; Brian Mac Namee (Inf. Sci., 2019)

Detection and Categorisation of Multilevel High-sensitivity Cardiovascular Biomarkers from Lateral Flow Immunoassay Images via Recurrent Neural Networks. - Min Jing; Donal McLaughlin; David Steele; Sara McNamee; Brian MacNamee; Patrick Cullen; Dewar D. Finlay; James McLaughlin 001 (BIOIMAGING, 2020)

Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings. - John Mitros; Arjun Pakrashi; Brian Mac Namee (ECCV Workshops (1), 2020)

Enhance Categorisation Of Multilevel High-Sensitivity Cardiovascular Biomarkers From Lateral Flow Immunoassay Images Via Neural Networks And Dynamic Time Warping. - Min Jing; Brian Mac Namee; Donal McLaughlin; David Steele; Sara McNamee; Patrick Cullen; Dewar D. Finlay; James McLaughlin 001 (ICIP, 2020)

Diverging Divergences: Examining Variants of Jensen Shannon Divergence for Corpus Comparison Tasks. - Jinghui Lu; Maeve Henchion; Brian Mac Namee (LREC, 2020)

ZeChipC: Time Series Interpolation Method Based on Lebesgue Sampling. - Luis Miralles-Pechuán; Matthieu Bellucci; Muhammad Atif Qureshi 001; Brian Mac Namee (MICAI (1), 2020)

Valve Health Identification Using Sensors and Machine Learning Methods. - Muhammad Atif Qureshi 001; Luis Miralles-Pechuán; Jason Payne; Ronan O'Malley; Brian Mac Namee (IoT Streams/ITEM@PKDD/ECML, 2020)

KalmanTune: A Kalman Filter Based Tuning Method to Make Boosted Ensembles Robust to Class-Label Noise. - Arjun Pakrashi; Brian Mac Namee (IEEE Access, 2020)

Overlapping community finding with noisy pairwise constraints. - Elham Abdullah Alghamdi; Ellen Rushe; Brian Mac Namee; Derek Greene (Appl. Netw. Sci., 2020)

Investigating the Effectiveness of Representations Based on Pretrained Transformer-based Language Models in Active Learning for Labelling Text Datasets. - Jinghui Lu; Brian MacNamee (CoRR, 2020)

Deep Context-Aware Novelty Detection. - Ellen Rushe; Brian Mac Namee (CoRR, 2020)

Can We Detect Mastitis earlier than Farmers? - Cathal Ryan; Christophe Guéret; Donagh Berry; Brian Mac Namee (CoRR, 2020)

A Hybrid Agent-Based and Equation Based Model for the Spread of Infectious Diseases. - Elizabeth Hunter; Brian Mac Namee; John D. Kelleher (J. Artif. Soc. Soc. Simul., 2020)

Machine Learning in Space: A Review of Machine Learning Algorithms and Hardware for Space Applications. - James Murphy; John E. Ward; Brian Mac Namee (AICS, 2021)

Adaptation of Compositional Data Analysis in Deep Learning to Predict Pasture Biomass Proportions. - Badri Narayanan 002; Mohamed Saadeldin; Paul Albert; Kevin McGuinness; Noel E. O'Connor; Brian Mac Namee (AICS, 2021)

Bias Bubbles: Using Semi-Supervised Learning to Measure How Many Biased News Articles Are Around Us. - Qin Ruan; Brian Mac Namee; Ruihai Dong (AICS, 2021)

A Sentence-Level Hierarchical BERT Model for Document Classification with Limited Labelled Data. - Jinghui Lu; Maeve Henchion; Ivan Bacher; Brian Mac Namee (DS, 2021)

Semi-supervised dry herbage mass estimation using automatic data and synthetic images. - Paul Albert; Mohamed Saadeldin; Badri Narayanan 002; Brian Mac Namee; Deirdre Hennessy; Aisling O'Connor; Noel E. O'Connor; Kevin McGuinness (ICCVW, 2021)

On the Importance of Regularisation and Auxiliary Information in OOD Detection. - John Mitros; Brian Mac Namee (ICONIP (6), 2021)

An Orthogonal Classification Layer with Kasami Sequences for Discriminative Feature Learning in Neural Networks. - Mohamed Saadeldin; Brian MacNamee (ICTAI, 2021)

ML-NCA: Multi-label Neighbourhood Component Analysis. - Arjun Pakrashi; Payel Sadhukhan; Brian Mac Namee (LIDTA@ECML/PKDD, 2021)

Academic Performance Prediction Based on Multisource, Multifeature Behavioral Data. - Liang Zhao 016; Kun Chen; Jie Song; Xiaoliang Zhu; Jianwen Sun; Brian Caulfield 001; Brian Mac Namee (IEEE Access, 2021)

Predicting Illness for a Sustainable Dairy Agriculture: Predicting and Explaining the Onset of Mastitis in Dairy Cows. - Cathal Ryan; Christophe Guéret; Donagh Berry; Medb Corcoran; Mark T. Keane; Brian Mac Namee (CoRR, 2021)

Extracting Pasture Phenotype and Biomass Percentages using Weakly Supervised Multi-target Deep Learning on a Small Dataset. - Badri Narayanan 002; Mohamed Saadeldin; Paul Albert; Kevin McGuinness; Brian Mac Namee (CoRR, 2021)

On the Importance of Regularisation & Auxiliary Information in OOD Detection. - John Mitros; Brian Mac Namee (CoRR, 2021)

Pseudo-labelling Enhanced Media Bias Detection. - Qin Ruan; Brian Mac Namee; Ruihai Dong (CoRR, 2021)

A multi-label cascaded neural network classification algorithm for automatic training and evolution of deep cascaded architecture. - Arjun Pakrashi; Brian Mac Namee (Expert Syst. J. Knowl. Eng., 2021)

COVID-19 modelling by time-varying transmission rate associated with mobility trend of driving via Apple Maps. - Min Jing; Kok Yew Ng; Brian Mac Namee; Pardis Biglarbeigi; Rob Brisk; Raymond R. Bond; Dewar D. Finlay; James McLaughlin 001 (J. Biomed. Informatics, 2021)

A Rationale-Centric Framework for Human-in-the-loop Machine Learning. - Jinghui Lu; Linyi Yang; Brian MacNamee; Yue Zhang 004 (ACL (1), 2022)

AI and ML in School Level Computing Education: Who, What and Where? - Joyce Mahon; Brett A. Becker; Brian Mac Namee (AICS, 2022)

Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation. - Paul Albert; Mohamed Saadeldin; Badri Narayanan 002; Brian Mac Namee; Deirdre Hennessy; Noel E. O'Connor; Kevin McGuinness (CVPR Workshops, 2022)

Interpretable Identification of Mild Cognitive Impairment Progression Using Stereotactic Surface Projections. - Misgina Tsighe Hagos; Ronan P. Killeen; Kathleen M. Curran; Brian Mac Namee (PAIS@ECAI, 2022)

Impact of Feedback Type on Explanatory Interactive Learning. - Misgina Tsighe Hagos; Kathleen M. Curran; Brian Mac Namee (ISMIS, 2022)

Deep Contextual Novelty Detection with Context Prediction. - Ellen Rushe; Brian Mac Namee (LIDTA, 2022)

A Novel Machine Learning and Artificial Intelligence Course for Secondary School Students. - Joyce Mahon; Keith Quille; Brian Mac Namee; Brett A. Becker (SIGCSE (2), 2022)

Random Walk-steered Majority Undersampling. - Payel Sadhukhan; Arjun Pakrashi; Brian Mac Namee (SMC, 2022)

The Deep Radial Basis Function Data Descriptor (D-RBFDD) Network: A One-Class Neural Network for Anomaly Detection. - Mehran Hossein Zadeh Bazargani; Arjun Pakrashi; Brian Mac Namee (IEEE Access, 2022)

Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation. - Paul Albert; Mohamed Saadeldin; Badri Narayanan 002; Jaime B. Fernandez; Brian Mac Namee; Deirdre Hennessy; Noel E. O'Connor; Kevin McGuinness (CoRR, 2022)

Utilizing unsupervised learning to improve sward content prediction and herbage mass estimation. - Paul Albert; Mohamed Saadeldin; Badri Narayanan 002; Brian Mac Namee; Deirdre Hennessy; Aisling H. O'Connor; Noel E. O'Connor; Kevin McGuinness (CoRR, 2022)

What Makes Pre-trained Language Models Better Zero/Few-shot Learners? - Jinghui Lu; Rui Zhao; Brian Mac Namee; Dongsheng Zhu; Weidong Han 002; Fei Tan 002 (CoRR, 2022)

Identifying Spurious Correlations and Correcting them with an Explanation-based Learning. - Misgina Tsighe Hagos; Kathleen M. Curran; Brian Mac Namee (CoRR, 2022)

PUnifiedNER: A Prompting-Based Unified NER System for Diverse Datasets. - Jinghui Lu; Rui Zhao; Brian Mac Namee; Fei Tan 002 (AAAI, 2023)

Do Cows Have Fingerprints? Using Time Series Techniques and Milk Flow Profiles to Characterise Cow Milking Performance and Detect Health Issues. - Changhong Jin; John Upton; Brian Mac Namee (AALTD@ECML/PKDD, 2023)

What Makes Pre-trained Language Models Better Zero-shot Learners? - Jinghui Lu; Dongsheng Zhu; Weidong Han 002; Rui Zhao; Brian Mac Namee; Fei Tan 002 (ACL (1), 2023)

Reducing Media Bias in News Headlines. - Qin Ruan; Brian Mac Namee; Ruihai Dong (AICS, 2023)

Unlearning Spurious Correlations in Chest X-Ray Classification. - Misgina Tsighe Hagos; Kathleen M. Curran; Brian Mac Namee (DS, 2023)

Investigating Temporal Features of Carotid Intima-Media Thickness from Ultrasound Imaging with Recurrent Neural Networks. - Min Jing; Kathryn Owen; Brian Mac Namee; Iab B. A. Menown; James McLaughlin 001 (EMBC, 2023)

Integrating Unsupervised Clustering and Label-Specific Oversampling to Tackle Imbalanced Multi-Label Data. - Payel Sadhukhan; Arjun Pakrashi; Sarbani Palit; Brian Mac Namee (ICAART (2), 2023)

Distance-Aware eXplanation Based Learning. - Misgina Tsighe Hagos; Niamh Belton; Kathleen M. Curran; Brian Mac Namee (ICTAI, 2023)

Interpretable Weighted Siamese Network to Predict the Time to Onset of Alzheimer's Disease from MRI Images. - Misgina Tsighe Hagos; Niamh Belton; Ronan P. Killeen; Kathleen M. Curran; Brian Mac Namee (SGAI Conf., 2023)

Exploring Optimal Configurations in Active Learning for Medical Imaging. - Alec Parise; Brian Mac Namee (SGAI Conf., 2023)

Unveiling the Relationship Between News Recommendation Algorithms and Media Bias: A Simulation-Based Analysis of the Evolution of Bias Prevalence. - Qin Ruan; Brian Mac Namee; Ruihai Dong (SGAI Conf., 2023)

No More Pencils No More Books: Capabilities of Generative AI on Irish and UK Computer Science School Leaving Examinations. - Joyce Mahon; Brian Mac Namee; Brett A. Becker (UKICER, 2023)

The Influence of Media Bias on News Recommender Systems. - Qin Ruan; Brian Mac Namee; Ruihai Dong (UMAP, 2023)

Weighted Siamese Network to Predict the Time to Onset of Alzheimer's Disease from MRI Images. - Misgina Tsighe Hagos; Niamh Belton; Ronan P. Killeen; Kathleen M. Curran; Brian Mac Namee (CoRR, 2023)

Learning from Exemplary Explanations. - Misgina Tsighe Hagos; Kathleen M. Curran; Brian Mac Namee (CoRR, 2023)

Explaining Knock-on Effects of Bias Mitigation. - Svetoslav Nizhnichenkov; Rahul Nair; Elizabeth Daly; Brian Mac Namee (CoRR, 2023)

CowMesh: a data-mesh architecture to unify dairy industry data for prediction and monitoring. - Arjun Pakrashi; Duncan Wallace; Brian Mac Namee; Derek Greene; Christophe Guéret (Frontiers Artif. Intell., 2023)

Real-time bidding campaigns optimization using user profile settings. - Luis Miralles-Pechuán; Muhammad Atif Qureshi 001; Brian Mac Namee (Electron. Commer. Res., 2023)

ML-KFHE: Multi-label Ensemble Classification Algorithm Exploiting Sensor Fusion Properties of the Kalman Filter. - Arjun Pakrashi; Brian Mac Namee (SN Comput. Sci., 2023)

Mapping Upper Secondary Computer Science Specifications Against UNESCO's Framework of AI Learning Outcomes. - Joyce Mahon; Brian Mac Namee; Brett A. Becker (AICS, 2024)

Autonomous Satellite Health Monitoring using EIRSAT-1 Telemetry. - James Murphy; Muhammad Deedahwar Mazhar Qureshi; Jake O'Brien; Brian Mac Namee (AICS, 2024)

Image Retrieval with Short Text Queries. - Ojas Rane; Brian Mac Namee; Conor Nugent (AICS, 2024)

Deploying Machine Learning Anomaly Detection Models to Flight Ready AI Boards. - James Murphy; Maria Buckley; Léonie Buckley; Adam Taylor; Jake O'Brien; Brian Mac Namee (CVPR Workshops, 2024)

Explainable Interactive Machine Learning Using Prototypical Part Networks for Medical Image Analysis. - Brian Mac Namee (HHAI, 2024)

Guidelines for the Evolving Role of Generative AI in Introductory Programming Based on Emerging Practice. - Joyce Mahon; Brian Mac Namee; Brett A. Becker (ITiCSE (1), 2024)

Post Primary Teachers' Perspectives on Machine Learning and Artificial Intelligence in the Leaving Certificate Computer Science Curriculum. - Joyce Mahon; Brett A. Becker; Brian Mac Namee; Juho Leinonen 001 (Koli Calling, 2024)

PaDeLLM-NER: Parallel Decoding in Large Language Models for Named Entity Recognition. - Jinghui Lu; Yanjie Wang; Ziwei Yang; Xuejing Liu; Brian Mac Namee; Can Huang (NeurIPS, 2024)

Rewriting Bias: Mitigating Media Bias in News Recommender Systems through Automated Rewriting. - Qin Ruan; Jin Xu; Susan Leavy; Brian Mac Namee; Ruihai Dong (UMAP, 2024)

The Effects of Media Bias on News Recommendations. - Qin Ruan; Brian Mac Namee; Ruihai Dong (IEEE Access, 2024)

Rewritten Media Bias News Headlines. - Qin Ruan; Jin Xu; Susan Leavy; Brian Mac Namee; Ruihai Dong (Zenodo, 2024)

International Mobility for PhD Students: Key Learnings. - Cecilia O. Alm; Reynold Bailey; Sarah Jane Delany; Georgiana Ifrim; Brian Mac Namee; Esa M. Rantanen; Ferat Sahin (SIGCSE (2), 2025)