| MobileNetV4: Universal models for the mobile ecosystem D Qin, C Leichner, M Delakis, M Fornoni, S Luo, F Yang, W Wang, ... European Conference on Computer Vision, 78-96, 2024 | 642* | 2024 |
| 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 | 415 | 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 | 384 | 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 | 353 | 2021 |
| 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, 5320-5347, 2023 | 195 | 2023 |
| 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 | 188 | 2022 |
| 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 | 136 | 2017 |
| 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 | 91 | 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 | 81* | 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 | 80 | 2021 |
| 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 | 66 | 2023 |
| 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 | 64 | 2023 |
| 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 | 63 | 2022 |
| Few-shot keyword spotting in any language M Mazumder, C Banbury, J Meyer, P Warden, VJ Reddi Proceedings of Interspeech, 2021 | 63 | 2021 |
| Is tinyml sustainable? S Prakash, M Stewart, C Banbury, M Mazumder, P Warden, B Plancher, ... Communications of the ACM 66 (11), 68-77, 2023 | 47 | 2023 |
| Machine learning sensors P Warden, M Stewart, B Plancher, S Katti, VJ Reddi Communications of the ACM 66 (11), 25-28, 2023 | 36 | 2023 |
| WinSpot: GUI grounding benchmark with multimodal large language models Z Hui, Y Li, D Zhao, C Banbury, T Chen, K Koishida Proceedings of the 63rd Annual Meeting of the Association for Computational …, 2025 | 11* | 2025 |
| Wake vision: A tailored dataset and benchmark suite for tinyml computer vision applications C Banbury, E Njor, AM Garavagno, M Mazumder, M Stewart, P Warden, ... arXiv preprint arXiv:2405.00892, 2024 | 8* | 2024 |
| 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 | 8 | 2019 |
| Automatic joint structured pruning and quantization for efficient neural network training and compression X Qu, D Aponte, C Banbury, DP Robinson, T Ding, K Koishida, I Zharkov, ... Proceedings of the Computer Vision and Pattern Recognition Conference, 15234 …, 2025 | 7 | 2025 |
