| Benchmarking tinyml systems: Challenges and direction CR Banbury, VJ Reddi, M Lam, W Fu, A Fazel, J Holleman, X Huang, ... arXiv preprint arXiv:2003.04821, 2020 | 293 | 2020 |
| Micronets: Neural network architectures for deploying tinyml applications on commodity microcontrollers C Banbury, C Zhou, I Fedorov, R Matas, U Thakker, D Gope, ... Proceedings of machine learning and systems 3, 517-532, 2021 | 262 | 2021 |
| Mlperf Tiny Benchmark C Banbury, VJ Reddi, P Torelli, J Holleman, N Jeffries, C Kiraly, P Montino, ... Proceedings of the Neural Information Processing Systems Track on Datasets …, 2021 | 198 | 2021 |
| The performance of the hot end in a plasticating 3D printer ME Mackay, ZR Swain, CR Banbury, DD Phan, DA Edwards Journal of Rheology 61 (2), 229-236, 2017 | 122 | 2017 |
| Dataperf: Benchmarks for data-centric ai development M Mazumder, C Banbury, X Yao, B Karlaš, W Gaviria Rojas, S Diamos, ... Advances in Neural Information Processing Systems 36, 2024 | 112 | 2024 |
| Edge impulse: An mlops platform for tiny machine learning S Hymel, C Banbury, D Situnayake, A Elium, C Ward, M Kelcey, ... arXiv preprint arXiv:2212.03332, 2022 | 82 | 2022 |
| Widening access to applied machine learning with tinyml VJ Reddi, B Plancher, S Kennedy, L Moroney, P Warden, A Agarwal, ... arXiv preprint arXiv:2106.04008, 2021 | 71 | 2021 |
| Tiny robot learning (tinyrl) for source seeking on a nano quadcopter BP Duisterhof, S Krishnan, JJ Cruz, CR Banbury, W Fu, A Faust, ... 2021 IEEE International Conference on Robotics and Automation (ICRA), 7242-7248, 2021 | 65* | 2021 |
| Multilingual spoken words corpus M Mazumder, S Chitlangia, C Banbury, Y Kang, JM Ciro, K Achorn, ... Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021 | 53 | 2021 |
| Few-shot keyword spotting in any language M Mazumder, C Banbury, J Meyer, P Warden, VJ Reddi Proceedings of Interspeech, 2021 | 40 | 2021 |
| Tiny robot learning: Challenges and directions for machine learning in resource-constrained robots SM Neuman, B Plancher, BP Duisterhof, S Krishnan, C Banbury, ... 2022 IEEE 4th International Conference on Artificial Intelligence Circuits …, 2022 | 36 | 2022 |
| Cfu playground: Full-stack open-source framework for tiny machine learning (tinyml) acceleration on fpgas S Prakash, T Callahan, J Bushagour, C Banbury, AV Green, P Warden, ... 2023 IEEE International Symposium on Performance Analysis of Systems and …, 2023 | 34 | 2023 |
| MobileNetV4-Universal Models for the Mobile Ecosystem D Qin, C Leichner, M Delakis, M Fornoni, S Luo, F Yang, W Wang, ... arXiv preprint arXiv:2404.10518, 2024 | 32 | 2024 |
| Xrbench: An extended reality (xr) machine learning benchmark suite for the metaverse H Kwon, K Nair, J Seo, J Yik, D Mohapatra, D Zhan, J Song, P Capak, ... Proceedings of Machine Learning and Systems 5, 1-20, 2023 | 24 | 2023 |
| Machine learning sensors P Warden, M Stewart, B Plancher, S Katti, VJ Reddi Communications of the ACM 66 (11), 25-28, 2023 | 21 | 2023 |
| Is TinyML Sustainable? S Prakash, M Stewart, C Banbury, M Mazumder, P Warden, B Plancher, ... Communications of the ACM 66 (11), 68-77, 2023 | 18 | 2023 |
| Mobilenetv4-universal models for the mobile ecosystem. arXiv 2024 D Qin, C Leichner, M Delakis, M Fornoni, S Luo, F Yang, W Wang, ... arXiv preprint arXiv:2404.10518, 0 | 14 | |
| Maximal 3D printing extrusion rates DA Edwards, ME Mackay, ZR Swain, CR Banbury, DD Phan IMA Journal of Applied Mathematics 84 (5), 1022-1043, 2019 | 5 | 2019 |
| Precision Batching: Bitserial Decomposition for Efficient Neural Network Inference on GPUs M Lam, Z Yedidia, CR Banbury, VJ Reddi 2021 30th International Conference on Parallel Architectures and Compilation …, 2021 | 4* | 2021 |
| HESSO: Towards Automatic Efficient and User Friendly Any Neural Network Training and Pruning T Chen, X Qu, D Aponte, C Banbury, J Ko, T Ding, Y Ma, V Lyapunov, ... arXiv preprint arXiv:2409.09085, 2024 | | 2024 |
