Comparison of accelerometer-based energy expenditure estimation algorithms. - Niall Twomey; Stephen Faul; William P. Marnane (PervasiveHealth, 2010)

Allergy detection with statistical modelling of HRV-based non-reaction baseline features. - Niall Twomey; Andrey Temko; Jonathan O'B. Hourihane; William P. Marnane (ISABEL, 2011)

A Machine Learning Approach to Objective Cardiac Event Detection. - Niall Twomey; Peter A. Flach (CISIS, 2014)

Automated Detection of Perturbed Cardiac Physiology During Oral Food Allergen Challenge in Children. - Niall Twomey; Andrey Temko; Jonathan O'B. Hourihane; William P. Marnane (IEEE J. Biomed. Health Informatics, 2014)

Bayesian Modelling of the Temporal Aspects of Smart Home Activity with Circular Statistics. - Tom Diethe; Niall Twomey; Peter A. Flach (ECML/PKDD (2), 2015)

An RSSI-based wall prediction model for residential floor map construction. - Xenofon Fafoutis; Evangelos Mellios; Niall Twomey; Tom Diethe; Geoffrey S. Hilton; Robert J. Piechocki (WF-IoT, 2015)

Bridging e-Health and the Internet of Things: The SPHERE Project. - Ni Zhu; Tom Diethe; Massimo Camplani; Lili Tao; Alison Burrows; Niall Twomey; Dritan Kaleshi; Majid Mirmehdi; Peter A. Flach; Ian Craddock (IEEE Intell. Syst., 2015)

Active transfer learning for activity recognition. - Tom Diethe; Niall Twomey; Peter A. Flach (ESANN, 2016)

BDL.NET: Bayesian dictionary learning in Infer.NET. - Tom Diethe; Niall Twomey; Peter A. Flach (MLSP, 2016)

The SPHERE Challenge: Activity Recognition with Multimodal Sensor Data. - Niall Twomey; Tom Diethe; Meelis Kull; Hao Song 007; Massimo Camplani; Sion L. Hannuna; Xenofon Fafoutis; Ni Zhu; Pete Woznowski; Peter A. Flach; Ian Craddock (CoRR, 2016)

On the need for structure modelling in sequence prediction. - Niall Twomey; Tom Diethe; Peter A. Flach (Mach. Learn., 2016)

Talk, text or tag? - Przemyslaw Woznowski; Emma Tonkin; Pawel Laskowski; Niall Twomey; Kristina Y. Yordanova; Alison Burrows (PerCom Workshops, 2017)

Probabilistic Sensor Fusion for Ambient Assisted Living. - Tom Diethe; Niall Twomey; Meelis Kull; Peter A. Flach; Ian Craddock (CoRR, 2017)

Unsupervised learning of sensor topologies for improving activity recognition in smart environments. - Niall Twomey; Tom Diethe; Ian Craddock; Peter A. Flach (Neurocomputing, 2017)

Anomaly detection in star light curves using hierarchical Gaussian processes. - Haoyan Chen; Tom Diethe; Niall Twomey; Peter A. Flach (ESANN, 2018)

Person Identification and Discovery With Wrist Worn Accelerometer Data. - Ryan McConville; Raúl Santos-Rodríguez; Niall Twomey (ESANN, 2018)

Efficient approximate representations for computationally expensive features. - Raúl Santos-Rodríguez; Niall Twomey (ESANN, 2018)

On-Board Feature Extraction from Acceleration Data for Activity Recognition. - Atis Elsts; Ryan McConville; Xenofon Fafoutis; Niall Twomey; Robert J. Piechocki; Raúl Santos-Rodriguez; Ian Craddock (EWSN, 2018)

Releasing eHealth Analytics into the Wild: Lessons Learnt from the SPHERE Project. - Tom Diethe; Mike Holmes; Meelis Kull; Miquel Perelló-Nieto; Kacper Sokol; Hao Song 007; Emma Tonkin; Niall Twomey; Peter A. Flach (KDD, 2018)

Label Propagation for Learning with Label proportions. - Rafael Poyiadzi; Raúl Santos-Rodríguez; Niall Twomey (MLSP, 2018)

A Comprehensive Study of Activity Recognition Using Accelerometers. - Niall Twomey; Tom Diethe; Xenofon Fafoutis; Atis Elsts; Ryan McConville; Peter A. Flach; Ian Craddock (Informatics, 2018)

Talk, Text, Tag? Understanding Self-Annotation of Smart Home Data from a User's Perspective. - Emma Tonkin; Alison Burrows; Przemyslaw Woznowski; Pawel Laskowski; Kristina Y. Yordanova; Niall Twomey; Ian Craddock (Sensors, 2018)

Active Learning with Label Proportions. - Rafael Poyiadzi; Raúl Santos-Rodríguez; Niall Twomey (ICASSP, 2019)

Ordinal Regression as Structured Classification. - Niall Twomey; Rafael Poyiadzi; Callum Mann; Raúl Santos-Rodríguez (CoRR, 2019)

HyperStream: a Workflow Engine for Streaming Data. - Tom Diethe; Meelis Kull; Niall Twomey; Kacper Sokol; Hao Song 007; Miquel Perelló-Nieto; Emma Tonkin; Peter A. Flach (CoRR, 2019)

An application of hierarchical Gaussian processes to the detection of anomalies in star light curves. - Niall Twomey; Haoyan Chen; Tom Diethe; Peter A. Flach (Neurocomputing, 2019)

Detecting Signatures of Early-stage Dementia with Behavioural Models Derived from Sensor Data. - Rafael Poyiadzi; Weisong Yang; Yoav Ben-Shlomo; Ian Craddock; Liz Coulthard; Raúl Santos-Rodríguez; James Selwood; Niall Twomey (AAI4H@ECAI, 2020)

Neural ODEs with Stochastic Vector Field Mixtures. - Niall Twomey; Michal Kozlowski; Raúl Santos-Rodríguez (ECAI, 2020)

Towards Multi-Language Recipe Personalisation and Recommendation. - Niall Twomey; Mikhail Fain; Andrey Ponikar; Nadine Sarraf (RecSys, 2020)

Non-Linear Multiple Field Interactions Neural Document Ranking. - Kentaro Takiguchi; Niall Twomey; Luis M. Vaquero (CoRR, 2020)

Energy-efficient activity recognition framework using wearable accelerometers. - Atis Elsts; Niall Twomey; Ryan McConville; Ian Craddock (J. Netw. Comput. Appl., 2020)

Backretrieval: An Image-Pivoted Evaluation Metric for Cross-Lingual Text Representations Without Parallel Corpora. - Mikhail Fain; Niall Twomey; Danushka Bollegala (SIGIR, 2021)

Statistical Hypothesis Testing for Class-Conditional Label Noise. - Rafael Poyiadzi; Weisong Yang; Niall Twomey; Raúl Santos-Rodríguez (CoRR, 2021)

Multi-Field Models in Neural Recipe Ranking - An Early Exploratory Study. - Kentaro Takiguchi; Niall Twomey; Luis M. Vaquero (CoRR, 2021)

Towards Continuous Compounding Effects and Agile Practices in Educational Experimentation. - Luis M. Vaquero; Niall Twomey; Miguel Patricio Dias; Massimo Camplani; Robert Hardman (CoRR, 2021)

Detecting and Monitoring Behavioural Patterns in Individuals with Cognitive Disorders in the Home Environment with Partial Annotations. - Weisong Yang; Rafael Poyiadzi; Yoav Ben-Shlomo; Ian Craddock; Liz Coulthard; Raúl Santos-Rodríguez; James Selwood; Niall Twomey (Integrating Artificial Intelligence and IoT for Advanced Health Informatics, 2022)

Equitable Ability Estimation in Neurodivergent Student Populations with Zero-Inflated Learner Models. - Niall Twomey; Sarah McMullan; Anat Elhalal; Rafael Poyiadzi; Luis M. Vaquero (EDM, 2022)

Hypothesis Testing for Class-Conditional Label Noise. - Rafael Poyiadzi; Weisong Yang; Niall Twomey; Raúl Santos-Rodríguez (ECML/PKDD (3), 2022)

Low-Count Time Series Anomaly Detection. - Philipp Renz; Kurt Cutajar; Niall Twomey; Gavin K. C. Cheung; Hanting Xie (MLSP, 2023)

Hypothesis Testing for Class-Conditional Noise Using Local Maximum Likelihood. - Weisong Yang; Rafael Poyiadzi; Niall Twomey; Raúl Santos-Rodríguez (AAAI, 2024)

Inherently Interpretable Time Series Classification via Multiple Instance Learning. - Joseph Early; Gavin K. C. Cheung; Kurt Cutajar; Hanting Xie; Jas Kandola; Niall Twomey (ICLR, 2024)