| Virtual object placement in augmented reality environments GG Chiarella, DT Cunnington, JJ Wood, E Lee US Patent 10,917,613, 2021 | 26 | 2021 |
| FFNSL: feed-forward neural-symbolic learner D Cunnington, M Law, J Lobo, A Russo Machine Learning 112 (2), 515-569, 2023 | 20 | 2023 |
| Video censoring RK Ayers, GG Chiarella, DT Cunnington, EG Kelly, E Lee, AE Wishart US Patent 9,986,290, 2018 | 19 | 2018 |
| Neuro-Symbolic Learning of Answer Set Programs from Raw Data D Cunnington, M Law, J Lobo, A Russo arXiv preprint arXiv:2205.12735, 2022 | 18* | 2022 |
| A generative policy model for connected and autonomous vehicles D Cunnington, I Manotas, M Law, G de Mel, S Calo, E Bertino, A Russo 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 1558-1565, 2019 | 17 | 2019 |
| Agenp: An asgrammar-based generative policy framework S Calo, I Manotas, G de Mel, D Cunnington, M Law, D Verma, A Russo, ... Policy-based autonomic data governance, 3-20, 2019 | 17 | 2019 |
| Folding contactless card payment authentication GG Chiarella, DT Cunnington, E Lee, BT Roeger US Patent 10,269,020, 2019 | 13 | 2019 |
| The role of foundation models in neuro-symbolic learning and reasoning D Cunnington, M Law, J Lobo, A Russo International Conference on Neural-Symbolic Learning and Reasoning, 84-100, 2024 | 9 | 2024 |
| Distinguishing voice commands J Dunning, DT Cunnington, E Lee, GG Chiarella, JJ Wood US Patent 11,200,890, 2021 | 9 | 2021 |
| Distinguishing voice commands E Lee, DT Cunnington, GG Chiarella, JJ Wood US Patent 11,355,108, 2022 | 8 | 2022 |
| Voice command filtering E Lee, D Cunnington, JJ Wood, GG Chiarella US Patent 11,150,869, 2021 | 7 | 2021 |
| Ignoring trigger words in streamed media content E Lee, J Dunning, JJ Wood, GG Chiarella, DT Cunnington US Patent 11,238,856, 2022 | 5 | 2022 |
| HTML editing operations E Lee, JJ Wood, DT Cunnington, GG Chiarella US Patent 10,928,992, 2021 | 5 | 2021 |
| NSL: Hybrid interpretable learning from noisy raw data D Cunnington, A Russo, M Law, J Lobo, L Kaplan arXiv preprint arXiv:2012.05023, 2020 | 4 | 2020 |
| Generative policies for coalition systems-a symbolic learning framework E Bertino, A Russo, M Law, S Calo, I Manotas, D Verma, AA Jabal, ... 2019 IEEE 39th International Conference on Distributed Computing Systems …, 2019 | 4 | 2019 |
| Towards a Deeper Understanding of Concept Bottleneck Models Through End-to-End Explanation J Furby, D Cunnington, D Braines, A Preece arXiv preprint arXiv:2302.03578, 2023 | 3 | 2023 |
| Towards neural-symbolic learning to support human-agent operations D Cunnington, M Law, A Russo, J Lobo, L Kaplan 2021 IEEE 24th International Conference on Information Fusion (FUSION), 1-8, 2021 | 3 | 2021 |
| A demonstration of generative policy models in coalition environments D Cunnington, G White, M Law, G de Mel Advances in Practical Applications of Survivable Agents and Multi-Agent …, 2019 | 3 | 2019 |
| Can we Constrain Concept Bottleneck Models to Learn Semantically Meaningful Input Features? J Furby, D Cunnington, D Braines, A Preece arXiv preprint arXiv:2402.00912, 2024 | 2 | 2024 |
| Symbolic learning for material discovery D Cunnington, F Cipcigan, RNB Ferreira, J Booth arXiv preprint arXiv:2312.11487, 2023 | 2 | 2023 |