Dynotears: Structure learning from time-series data R Pamfil, N Sriwattanaworachai, S Desai, P Pilgerstorfer, K Georgatzis, ... International Conference on Artificial Intelligence and Statistics, 1595-1605, 2020 | 211 | 2020 |
Image analysis for cosmology: results from the GREAT10 star challenge TD Kitching, B Rowe, M Gill, C Heymans, R Massey, D Witherick, ... The Astrophysical Journal Supplement Series 205 (2), 12, 2013 | 59 | 2013 |
Recruitment and ongoing engagement in a UK smartphone study examining the association between weather and pain: cohort study KL Druce, J McBeth, SN van der Veer, DA Selby, B Vidgen, K Georgatzis, ... JMIR mHealth and uHealth 5 (11), e8162, 2017 | 56 | 2017 |
Auditing and achieving intersectional fairness in classification problems G Morina, V Oliinyk, J Waton, I Marusic, K Georgatzis arXiv preprint arXiv:1911.01468, 2019 | 41 | 2019 |
Inferring disease subtypes from clusters in explanation space MA Schulz, M Chapman-Rounds, M Verma, D Bzdok, K Georgatzis Scientific Reports 10 (1), 12900, 2020 | 32 | 2020 |
FIMAP: Feature importance by minimal adversarial perturbation M Chapman-Rounds, U Bhatt, E Pazos, MA Schulz, K Georgatzis Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 11433 …, 2021 | 20 | 2021 |
Input-output non-linear dynamical systems applied to physiological condition monitoring K Georgatzis, C Williams, C Hawthorne Machine Learning for Healthcare Conference, 1-16, 2016 | 11 | 2016 |
Effects of uncertainty on the quality of feature importance explanations T Shaikhina, U Bhatt, R Zhang, K Georgatzis, A Xiang, A Weller AAAI Workshop on Explainable Agency in Artificial Intelligence, 2021 | 10 | 2021 |
EMAP: Explanation by minimal adversarial perturbation M Chapman-Rounds, MA Schulz, E Pazos, K Georgatzis arXiv preprint arXiv:1912.00872, 2019 | 9 | 2019 |
Efficient optimization for data visualization as an information retrieval task J Peltonen, K Georgatzis 2012 IEEE International Workshop on Machine Learning for Signal Processing, 1-6, 2012 | 8 | 2012 |
Discriminative Switching Linear Dynamical Systems applied to Physiological Condition Monitoring K Georgatzis, CKI Williams Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence, 2015 | 7 | 2015 |
Detecting artifactual events in vital signs monitoring data P Lal, CKI Williams, K Georgatzis, C Hawthorne, P McMonagle, I Piper, ... Machine learning for healthcare technologies, 7, 2015 | 4 | 2015 |
Artefact in physiological data collected from patients with brain injury: Quantifying the problem and providing a solution using a factorial switching linear dynamical systems … K Georgatzis, P Lal, C Hawthorne, M Shaw, I Piper, C Tarbert, R Donald, ... Intracranial Pressure and Brain Monitoring XV, 301-305, 2016 | 3 | 2016 |
Benchmarking link analysis ranking methods in assistive environments K Georgatzis, P Papapetrou Proceedings of the 5th International Conference on PErvasive Technologies …, 2012 | 3 | 2012 |
Clusters in Explanation Space: Inferring disease subtypes from model explanations MA Schulz, M Chapman-Rounds, M Verma, D Bzdok, K Georgatzis arXiv preprint arXiv:1912.08755, 2019 | 2 | 2019 |
Machine Learning Methods for Regression in Astronomical Imaging K Georgatzis | 1 | 2011 |
Inferring disease subtypes from clusters in explanation space (vol 14, 6223, 2024) MA Schulz, M Chapman-Rounds, M Verma, D Bzdok, K Georgatzis SCIENTIFIC REPORTS 14 (1), 2024 | | 2024 |
Author Correction: Inferring disease subtypes from clusters in explanation space MA Schulz, M Chapman-Rounds, M Verma, D Bzdok, K Georgatzis Scientific Reports 14, 2024 | | 2024 |
Dynamical probabilistic graphical models applied to physiological condition monitoring K Georgatzis The University of Edinburgh, 2017 | | 2017 |
AB1138 Engagement in a uk smartphone study examining the assocation between weather and pain: preliminary results from cloudy with a chance of pain KL Druce, J McBeth, SN van der Veer, DA Selby, B Vidgen, K Georgatzis, ... Annals of the Rheumatic Diseases 76 (Suppl 2), 1453-1453, 2017 | | 2017 |