Journal articles
Ko, Y., Chadwick, A., Bates, D. and Mullins, R., 2021. Lane Compression: A Lightweight Lossless Compression Method for Machine Learning on Embedded Systems ACM Transactions on Embedded Computing Systems, v. 20
Doi: 10.1145/3431815
Shumailov, I., Zhao, Y., Bates, D., Papernot, N., Mullins, R. and Anderson, R., 2021. Sponge examples: Energy-latency attacks on neural networks Proceedings - 2021 IEEE European Symposium on Security and Privacy, Euro S and P 2021,
Doi: 10.1109/EuroSP51992.2021.00024
Mullins, RD. and Bates, D., 2018 (No publication date). A communication-centric low-power manycore processor with a configurable memory system IEEE Transactions on Computers,
Bates, D., Bradbury, A., Koltes, A. and Mullins, R., 2015. Exploiting Tightly-Coupled Cores Journal of Signal Processing Systems, v. 80
Doi: 10.1007/s11265-014-0944-6
Conference proceedings
Zhao, Y., Gao, X., Bates, D., Mullins, R. and Xu, C-Z., 2019 (Accepted for publication). Focused Quantization for Sparse CNNs Advances in Neural Information Processing Systems 2019,
Mullins, R. and Bates, D., 2018 (No publication date). Exploring a butterfly structured convolution method for neural networks
Mullins, R. and Bates, D., 2018 (No publication date). An adaptive scalable neural network accelerator capable of on-device learning
Maji, PP. and Mullins, R., 2017. ADaPT: optimizing CNN inference on IoT and mobile devices using approximately separable 1-D kernels IML '17 Proceedings of the 1st International Conference on Internet of Things and Machine Learning,
Doi: 10.1145/3109761.3109804
Bates, D., Bradbury, A., Koltes, A. and Mullins, R., 2013. Exploiting tightly-coupled cores Proceedings - 2013 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation, IC-SAMOS 2013,
Doi: 10.1109/SAMOS.2013.6621138
Working papers
Bates, D., Chadwick, A. and Mullins, R., 2016. Configurable memory systems for embedded many-core processors
Theses / dissertations
Books
Bates, D., 2013. Minecraft: Pi Edition Coding How-to
