| How Close Is Too Close? The Role of Feature Attributions in Discovering Counterfactual Explanations. | 0 | 0.34 | 2022 |
| FedSim: Similarity guided model aggregation for Federated Learning | 0 | 0.34 | 2022 |
| Adapting Semantic Similarity Methods for Case-Based Reasoning in the Cloud. | 0 | 0.34 | 2022 |
| DisCERN: Discovering Counterfactual Explanations using Relevance Features from Neighbourhoods | 0 | 0.34 | 2021 |
| Actionable Feature Discovery in Counterfactuals using Feature Relevance Explainers. | 0 | 0.34 | 2021 |
| Learning to Recognise Exercises in the Self-Management of Low Back Pain. | 0 | 0.34 | 2020 |
| A knowledge-light approach to personalised and open-ended human activity recognition. | 0 | 0.34 | 2020 |
| Evaluating the Transferability of Personalised Exercise Recognition Models. | 0 | 0.34 | 2020 |
| Learning to compare with few data for personalised human activity recognition. | 0 | 0.34 | 2020 |
| Personalised Meta-Learning for Human Activity Recognition with Few-Data. | 0 | 0.34 | 2020 |
| Learning to Self-Manage by Intelligent Monitoring, Prediction and Intervention. | 0 | 0.34 | 2019 |
| Workshop preface. | 0 | 0.34 | 2019 |
| Human Activity Recognition with Deep Metric Learners. | 0 | 0.34 | 2019 |
| Improving kNN for Human Activity Recognition with Privileged Learning Using Translation Models. | 0 | 0.34 | 2018 |
| Zero-Shot Learning with Matching Networks for Open-Ended Human Activity Recognition. | 0 | 0.34 | 2018 |
