Use fewer instances of the letter “i”: Toward writing style anonymization AWE McDonald, S Afroz, A Caliskan, A Stolerman, R Greenstadt Privacy Enhancing Technologies: 12th International Symposium, PETS 2012 …, 2012 | 130 | 2012 |
Anonymouth revamped: Getting closer to stylometric anonymity AWE McDonald, J Ulman, M Barrowclift, R Greenstadt PETools: Workshop on Privacy Enhancing Tools 20, 2013 | 14 | 2013 |
Short time‐span ice tracking using sequential AVHRR imagery RF Vincent, RF Marsden, A McDonald Atmosphere-Ocean 39 (3), 279-288, 2001 | 12 | 2001 |
Deepextrema: A deep learning approach for forecasting block maxima in time series data AH Galib, A McDonald, T Wilson, L Luo, PN Tan arXiv preprint arXiv:2205.02441, 2022 | 8 | 2022 |
Comet flows: Towards generative modeling of multivariate extremes and tail dependence A McDonald, PN Tan, L Luo arXiv preprint arXiv:2205.01224, 2022 | 8 | 2022 |
Sparse Super-Regular Networks AWE McDonald, A Shokoufandeh 18th IEEE International Conference on Machine Learning and Applications, 2019 | 5 | 2019 |
Beyond point prediction: Capturing zero-inflated & heavy-tailed spatiotemporal data with deep extreme mixture models T Wilson, A McDonald, AH Galib, PN Tan, L Luo Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 4 | 2022 |
Directing chemotaxis-based spatial self-organisation via biased, random initial conditions S Grimes, L Bai, AWE McDonald, DE Breen International Journal of Parallel, Emergent and Distributed Systems 34 (4 …, 2019 | 3 | 2019 |
Surface marking technique to locate needle insertion point for ultrasound-guided neuraxial block BP Manickam, A McDonald BJA: British Journal of Anaesthesia 116 (4), 568-569, 2016 | 1 | 2016 |
Pushing the Limits of Subseasonal-to-Seasonal Sea Ice Forecasting with Deep Generative Modelling A McDonald, J Smith, P Yatsyshin, T Andersson, E Bowler, L van Zeeland, ... EGU24, 2024 | | 2024 |
Interrogating Sea Ice Predictability with Gradients HL Joakimsen, I Martinsen, LT Luppino, A McDonald, S Hosking, ... IEEE Geoscience and Remote Sensing Letters, 2024 | | 2024 |
Implementing Reproducible Environmental Data Science with Open Science: Lessons from the 1st Climate Informatics Reproducibility Challenge A McDonald, AC Castro, A Fouilloux, RB Lourenco, A Hyde, Y Rao AGU23, 2023 | | 2023 |
Deep Generative Modelling for Spatially Sharp Sea Ice Forecasting A McDonald, J Smith, P Yatsyshin, T Andersson, J Byrne, M Pérez-Ortiz, ... AGU Fall Meeting Abstracts 2023, GC21A-04, 2023 | | 2023 |
Self-Recover: Forecasting Block Maxima in Time Series from Predictors with Disparate Temporal Coverage Using Self-Supervised Learning. AH Galib, A McDonald, PN Tan, L Luo IJCAI, 3723-3731, 2023 | | 2023 |
Classifying sea ice in high-resolution SAR imagery using deep learning A McDonald, J Dimasaka, M Plumridge, J Torry, AC Zúñiga González, ... EGU General Assembly Conference Abstracts, EGU-9816, 2023 | | 2023 |
DeepExtrema: A Deep Learning Approach for Forecasting Block Maxima in Time Series Data A Hill Galib, A McDonald, T Wilson, L Luo, PN Tan arXiv e-prints, arXiv: 2205.02441, 2022 | | 2022 |
Exploiting Graphical Structures of Data and Neural Network Architectures AWE McDonald Drexel University, 2022 | | 2022 |
Towards Modeling Multivariate Extremes with Normalizing Flows A McDonald, PN Tan, L Luo AGU Fall Meeting Abstracts 2021, GC45F-0875, 2021 | | 2021 |
Graph Convolutions with Wavelets for Stream Temperature Forecasting A McDonald, S Haag, M Campagna, A Shokoufandeh AGU Fall Meeting 2020, 2020 | | 2020 |
Ortus: An Emotion-Driven Approach to (artificial) Biological Intelligence AWE McDonald, S Grimes, DE Breen European Conference on Artificial Life 2017, 14, 537-544, 2017 | | 2017 |