| 2025 | WACV | Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization. | Maxime Fontana, Michael W. Spratling, Miaojing Shi |
| 2024 | CVPR | One Prompt Word is Enough to Boost Adversarial Robustness for Pre-Trained Vision-Language Models. | Lin Li, Haoyan Guan, Jianing Qiu, Michael W. Spratling |
| 2024 | ICML | OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift. | Lin Li, Yifei Wang, Chawin Sitawarin, Michael W. Spratling |
| 2023 | ACML | The Importance of Anti-Aliasing in Tiny Object Detection. | Jinlai Ning, Michael W. Spratling |
| 2023 | ICLR | Data augmentation alone can improve adversarial training. | Lin Li, Michael W. Spratling |
| 2022 | ECCV | Registration Based Few-Shot Anomaly Detection. | Chaoqin Huang, Haoyan Guan, Aofan Jiang, Ya Zhang, Michael W. Spratling, Yanfeng Wang |
| 2022 | ICPR | CobNet: Cross Attention on Object and Background for Few-Shot Segmentation. | Haoyan Guan, Michael W. Spratling |
| 1998 | ESANN | A self-organising neural network for modelling cortical development. | Michael W. Spratling, Gillian Hayes |
| 1998 | ESANN | Learning sensory-motor cortical mappings without training. | Michael W. Spratling, Gillian Hayes |
| 1996 | BMVC | Uncalibrated Visual Servoing. | Michael W. Spratling, Roberto Cipolla |