Background Check: A General Technique to Build More Reliable and Versatile Classifiers. - Miquel Perelló-Nieto; Telmo de Menezes e Silva Filho; Meelis Kull; Peter A. Flach (ICDM, 2016)

Adapting Supervised Classification Algorithms to Arbitrary Weak Label Scenarios. - Miquel Perelló-Nieto; Raúl Santos-Rodríguez; Jesús Cid-Sueiro (IDA, 2017)

Analysis of Patient Domestic Activity in Recovery From Hip or Knee RePlacement Surgery: Modelling Wrist-worn Wearable RSSI and Accelerometer Data in The Wild. - Mike Holmes; Hao Song 007; Emma Tonkin; Miquel Perelló-Nieto; Sabrina Grant; Peter A. Flach (KDH@IJCAI, 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)

Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration. - Meelis Kull; Miquel Perelló-Nieto; Markus Kängsepp; Telmo de Menezes e Silva Filho; Hao Song 007; Peter A. Flach (NeurIPS, 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)

Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration. - Meelis Kull; Miquel Perelló-Nieto; Markus Kängsepp; Telmo de Menezes e Silva Filho; Hao Song 007; Peter A. Flach (CoRR, 2019)

Towards a Methodology for Acceptance Testing and Validation of Monitoring Bodyworn Devices. - Emma L. Tonkin; Miquel Perelló-Nieto; Haixia Bi; Antonis Vafeas (PerCom Workshops, 2020)

Recycling weak labels for multiclass classification. - Miquel Perelló-Nieto; Raúl Santos-Rodríguez; Dario García-García; Jesús Cid-Sueiro (Neurocomputing, 2020)

Modelling Patient Behaviour Using IoT Sensor Data: a Case Study to Evaluate Techniques for Modelling Domestic Behaviour in Recovery from Total Hip Replacement Surgery. - Michael Holmes; Miquel Perelló-Nieto; Hao Song 007; Emma Tonkin; Sabrina Grant; Peter A. Flach (J. Heal. Informatics Res., 2020)

On the Selection of Loss Functions Under Known Weak Label Models. - Daniel Bacaicoa-Barber; Miquel Perelló-Nieto; Raúl Santos-Rodríguez; Jesús Cid-Sueiro (ICANN (2), 2021)

Data labelling in the wild: annotating free-living activities and Parkinson's disease symptoms. - Catherine Morgan; Farnoosh Heidarivincheh; Ian Craddock; Ryan McConville; Miquel Perelló-Nieto; Emma L. Tonkin; Alessandro Masullo; Antonis Vafeas; Mickey Kim; Roisin McNaney; Gregory J. L. Tourte; Alan L. Whone (PerCom Workshops, 2021)

Classifier Calibration: How to assess and improve predicted class probabilities: a survey. - Telmo de Menezes e Silva Filho; Hao Song 007; Miquel Perelló-Nieto; Raúl Santos-Rodríguez; Meelis Kull; Peter A. Flach (CoRR, 2021)

Human Activity Recognition Based on Dynamic Active Learning. - Haixia Bi; Miquel Perelló-Nieto; Raúl Santos-Rodríguez; Peter A. Flach (IEEE J. Biomed. Health Informatics, 2021)

The Weak Supervision Landscape. - Rafael Poyiadzi; Daniel Bacaicoa-Barber; Jesús Cid-Sueiro; Miquel Perelló-Nieto; Peter A. Flach; Raúl Santos-Rodríguez (PerCom Workshops, 2022)

When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations. - Taku Yamagata; Emma L. Tonkin; Benjamin Arana Sanchez; Ian Craddock; Miquel Perelló-Nieto; Raúl Santos-Rodríguez; Weisong Yang; Peter A. Flach (PerCom Workshops, 2023)

Classifier calibration: a survey on how to assess and improve predicted class probabilities. - Telmo de Menezes e Silva Filho; Hao Song 007; Miquel Perelló-Nieto; Raúl Santos-Rodríguez; Meelis Kull; Peter A. Flach (Mach. Learn., 2023)

An active semi-supervised deep learning model for human activity recognition. - Haixia Bi; Miquel Perelló-Nieto; Raúl Santos-Rodríguez; Peter A. Flach; Ian Craddock (J. Ambient Intell. Humaniz. Comput., 2023)

Explaining a Probabilistic Prediction on the Simplex with Shapley Compositions. - Paul-Gauthier Noé; Miquel Perelló-Nieto; Jean-François Bonastre; Peter A. Flach (ECAI, 2024)

Exploring the Requirements of Clinicians for Explainable AI Decision Support Systems in Intensive Care. - Jeffrey N. Clark; Matthew Wragg; Emily Nielsen; Miquel Perelló-Nieto; Nawid Keshtmand; Michael Ambler; Shiv Sharma; Christopher P. Bourdeaux; Amberly Brigden; Raúl Santos-Rodríguez (CoRR, 2024)