| Semi-supervised learning with deep embedded clustering for image classification and segmentation J Enguehard, P O’Halloran, A Gholipour Ieee Access 7, 11093-11104, 2019 | 102 | 2019 |
| Neural temporal point processes for modelling electronic health records J Enguehard, D Busbridge, A Bozson, C Woodcock, N Hammerla Machine Learning for Health, 85-113, 2020 | 45 | 2020 |
| Sequential integrated gradients: a simple but effective method for explaining language models J Enguehard arXiv preprint arXiv:2305.15853, 2023 | 40 | 2023 |
| Lung nodule malignancy prediction in sequential ct scans: Summary of isbi 2018 challenge Y Balagurunathan, A Beers, M Mcnitt-Gray, L Hadjiiski, S Napel, ... IEEE transactions on medical imaging 40 (12), 3748-3761, 2021 | 30 | 2021 |
| Learning perturbations to explain time series predictions J Enguehard International Conference on Machine Learning, 9329-9342, 2023 | 18 | 2023 |
| Time Interpret: a Unified Model Interpretability Library for Time Series J Enguehard arXiv preprint arXiv:2306.02968, 2023 | 5 | 2023 |
| Neural language priors J Enguehard, D Busbridge, V Zhelezniak, N Hammerla arXiv preprint arXiv:1910.03492, 2019 | 4 | 2019 |
| Continuous Time Self Attention for Improved Computational Predictions JHT Enguehard, DW Busbridge, A Bozson US Patent App. 16/884,752, 2021 | 1 | 2021 |
| Using the Path of Least Resistance to Explain Deep Networks S Salek, J Enguehard arXiv preprint arXiv:2502.12108, 2025 | | 2025 |
