| Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration M Kull, M Perello-Nieto, M Kängsepp, T Silva Filho, H Song, P Flach Neurips 2019, 2019 | 381 | 2019 |
| Distribution Calibration for Regression H Song, T Diethe, M Kull, P Flach ICML 2019, 2019 | 127 | 2019 |
| Classifier calibration: a survey on how to assess and improve predicted class probabilities T Silva Filho, H Song, M Perello-Nieto, R Santos-Rodriguez, M Kull, ... Machine Learning 112 (9), 3211-3260, 2023 | 92 | 2023 |
| The SPHERE challenge: Activity recognition with multimodal sensor data N Twomey, T Diethe, M Kull, H Song, M Camplani, S Hannuna, X Fafoutis, ... arXiv preprint arXiv:1603.00797, 2016 | 89 | 2016 |
| Short paper: Time-dependent power load disaggregation with applications to daily activity monitoring H Song, G Kalogridis, Z Fan 2014 IEEE World Forum on Internet of Things (WF-IoT), 183-184, 2014 | 21 | 2014 |
| Releasing ehealth analytics into the wild: lessons learnt from the sphere project T Diethe, M Holmes, M Kull, M Perello Nieto, K Sokol, H Song, E Tonkin, ... Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 18 | 2018 |
| Subgroup discovery with proper scoring rules H Song, M Kull, P Flach, G Kalogridis Machine Learning and Knowledge Discovery in Databases: European Conference …, 2016 | 13 | 2016 |
| Modelling patient behaviour using IoT sensor data: a case study to evaluate techniques for modelling domestic behaviour in recovery from total hip replacement surgery M Holmes, MP Nieto, H Song, E Tonkin, S Grant, P Flach Journal of Healthcare Informatics Research 4, 238-260, 2020 | 11 | 2020 |
| Analysis of patient domestic activity in recovery from Hip or Knee replacement surgery: modelling wrist-worn wearable RSSI and Accelerometer data in the wild M Holmes, H Song, MP Nieto, E Tonkin, S Grant, P Flach The 3rd International Workshop on Knowledge Discovery in Healthcare Data …, 2018 | 8 | 2018 |
| Model-based Subgroup Discovery H Song University of Bristol, 2017 | 8 | 2017 |
| Non-Parametric Calibration of Probabilistic Regression H Song, M Kull, P Flach arXiv preprint arXiv:1806.07690, 2018 | 7 | 2018 |
| Efficient and robust model benchmarks with item response theory and adaptive testing H Song, P Flach International Journal of Interactive Multimedia and Artificial Intelligence …, 2021 | 6 | 2021 |
| Dataset Shift Detection with Model-Based Subgroup Discovery H Song, P Flach, G Kalogridis 2nd International Workshop on Learning over Multiple Contexts (LMCE 2015), 2015 | 4 | 2015 |
| A multi-sensor dataset with annotated activities of daily living recorded in a residential setting EL Tonkin, M Holmes, H Song, N Twomey, T Diethe, M Kull, ... Scientific Data 10 (1), 162, 2023 | 3 | 2023 |
| HyperStream: a Workflow Engine for Streaming Data T Diethe, M Kull, N Twomey, K Sokol, H Song, M Perelló-Nieto, E Tonkin, ... arXiv preprint arXiv:1908.02858, 2019 | 1 | 2019 |
| Model Reuse with Subgroup Discovery H Song, P Flach ECML-PKDD-DCs 2015, 1, 2015 | 1 | 2015 |
| Towards Efficient and Robust Model Benchmarks with Item Response Theory and Adaptive Testing H Song, P Flach ECAI 2020, 2020 | | 2020 |
Peter FlachProfessor of Artificial Intelligence, Department of Computer Science, University of BristolVerified email at bristol.ac.uk
