Learning to Seek: Autonomous Source Seeking with Deep Reinforcement Learning Onboard a Nano Drone Microcontroller. - Bardienus Pieter Duisterhof; Srivatsan Krishnan; Jonathan J. Cruz; Colby R. Banbury; William Fu; Aleksandra Faust; Guido C. H. E. de Croon; Vijay Janapa Reddi (CoRR, 2019)

Quantized Neural Network Inference with Precision Batching. - Maximilian Lam; Zachary Yedidia; Colby R. Banbury; Vijay Janapa Reddi (CoRR, 2020)

Benchmarking TinyML Systems: Challenges and Direction. - Colby R. Banbury; Vijay Janapa Reddi; Max Lam; William Fu; Amin Fazel; Jeremy Holleman; Xinyuan Huang; Robert Hurtado; David Kanter; Anton Lokhmotov; David A. Patterson 001; Danilo Pau; et al. (CoRR, 2020)

Precision Batching: Bitserial Decomposition for Efficient Neural Network Inference on GPUs. - Maximilian Lam; Zachary Yedidia; Colby R. Banbury; Vijay Janapa Reddi (PACT, 2021)

Tiny Robot Learning (tinyRL) for Source Seeking on a Nano Quadcopter. - Bardienus Pieter Duisterhof; Srivatsan Krishnan; Jonathan J. Cruz; Colby R. Banbury; William Fu; Aleksandra Faust; Guido C. H. E. de Croon; Vijay Janapa Reddi (ICRA, 2021)

Few-Shot Keyword Spotting in Any Language. - Mark Mazumder; Colby R. Banbury; Josh Meyer; Pete Warden; Vijay Janapa Reddi (Interspeech, 2021)

MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers. - Colby R. Banbury; Chuteng Zhou; Igor Fedorov; Ramon Matas Navarro; Urmish Thakker; Dibakar Gope; Vijay Janapa Reddi; Matthew Mattina; Paul N. Whatmough (MLSys, 2021)

MLPerf Tiny Benchmark. - Colby R. Banbury; Vijay Janapa Reddi; Peter Torelli; Nat Jeffries; Csaba Király 002; Jeremy Holleman; Pietro Montino; David Kanter; Pete Warden; Danilo Pau; Urmish Thakker; Antonio Torrini; et al. (NeurIPS Datasets and Benchmarks, 2021)

Multilingual Spoken Words Corpus. - Mark Mazumder; Sharad Chitlangia; Colby R. Banbury; Yiping Kang; Juan Ciro; Keith Achorn; Daniel Galvez; Mark Sabini; Peter Mattson; David Kanter; Greg Diamos; Pete Warden; et al. (NeurIPS Datasets and Benchmarks, 2021)

Widening Access to Applied Machine Learning with TinyML. - Vijay Janapa Reddi; Brian Plancher; Susan Kennedy; Laurence Moroney; Pete Warden; Anant Agarwal; Colby R. Banbury; Massimo Banzi; Matthew Bennett; Benjamin Brown; Sharad Chitlangia; Radhika Ghosal; et al. (CoRR, 2021)

MLPerf Tiny Benchmark. - Colby R. Banbury; Vijay Janapa Reddi; Peter Torelli; Jeremy Holleman; Nat Jeffries; Csaba Király 002; Pietro Montino; David Kanter; Sebastian Ahmed; Danilo Pau; Urmish Thakker; Antonio Torrini; et al. (CoRR, 2021)

Tiny Robot Learning: Challenges and Directions for Machine Learning in Resource-Constrained Robots. - Sabrina M. Neuman; Brian Plancher; Bardienus Pieter Duisterhof; Srivatsan Krishnan; Colby R. Banbury; Mark Mazumder; Shvetank Prakash; Jason Jabbour; Aleksandra Faust; Guido C. H. E. de Croon; Vijay Janapa Reddi (AICAS, 2022)

Machine Learning Sensors. - Pete Warden; Matthew Stewart; Brian Plancher; Colby R. Banbury; Shvetank Prakash; Emma Chen; Zain Asgar; Sachin Katti; Vijay Janapa Reddi (CoRR, 2022)

DataPerf: Benchmarks for Data-Centric AI Development. - Mark Mazumder; Colby R. Banbury; Xiaozhe Yao; Bojan Karlas; William Gaviria Rojas; Sudnya Frederick Diamos; Greg Diamos; Lynn He; Douwe Kiela; David Jurado; David Kanter; Rafael Mosquera; et al. (CoRR, 2022)

Edge Impulse: An MLOps Platform for Tiny Machine Learning. - Shawn Hymel; Colby R. Banbury; Daniel Situnayake; Alexander Elium; Carl Ward; Matthew Kelcey; Mathijs Baaijens; Mateusz Majchrzycki; Jenny Plunkett; David Tischler; Alessandro Grande; Louis Moreau; et al. (CoRR, 2022)

CFU Playground: Want a faster ML processor? Do it yourself! - Shvetank Prakash; Tim Callahan; Joseph Bushagour; Colby R. Banbury; Alan V. Green; Pete Warden; Tim Ansell; Vijay Janapa Reddi (DATE, 2023)

CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (TinyML) Acceleration on FPGAs. - Shvetank Prakash; Tim Callahan; Joseph Bushagour; Colby R. Banbury; Alan V. Green; Pete Warden; Tim Ansell; Vijay Janapa Reddi (ISPASS, 2023)

Edge Impulse: An MLOps Platform for Tiny Machine Learning. - Colby R. Banbury; Vijay Janapa Reddi; Alexander Elium; Shawn Hymel; David Tischler; Daniel Situnayake; Carl Ward; Louis Moreau; Jenny Plunkett; Matthew Kelcey; Mathijs Baaijens; Alessandro Grande; et al. (MLSys, 2023)

XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse. - Hyoukjun Kwon; Krishnakumar Nair; Jamin Seo; Jason Yik; Debabrata Mohapatra; Dongyuan Zhan; Jinook Song; Peter Capak; Peizhao Zhang; Peter Vajda; Colby R. Banbury; Mark Mazumder; et al. (MLSys, 2023)

DataPerf: Benchmarks for Data-Centric AI Development. - Mark Mazumder; Colby R. Banbury; Xiaozhe Yao; Bojan Karlas; William Gaviria Rojas; Sudnya Frederick Diamos; Greg Diamos; Lynn He; Alicia Parrish; Hannah Rose Kirk; Jessica Quaye; Charvi Rastogi; et al. (NeurIPS, 2023)

Is TinyML Sustainable? Assessing the Environmental Impacts of Machine Learning on Microcontrollers. - Shvetank Prakash; Matthew Stewart; Colby R. Banbury; Mark Mazumder; Pete Warden; Brian Plancher; Vijay Janapa Reddi (CoRR, 2023)

Is TinyML Sustainable? - Shvetank Prakash; Matthew Stewart; Colby R. Banbury; Mark Mazumder; Pete Warden; Brian Plancher; Vijay Janapa Reddi (Commun. ACM, 2023)

MobileNetV4: Universal Models for the Mobile Ecosystem. - Danfeng Qin; Chas Leichner; Manolis Delakis; Marco Fornoni; Shixin Luo; Fan Yang; Weijun Wang; Colby R. Banbury; Chengxi Ye; Berkin Akin; Vaibhav Aggarwal; Tenghui Zhu; et al. (ECCV (40), 2024)

Wake Vision: A Large-scale, Diverse Dataset and Benchmark Suite for TinyML Person Detection. - Colby R. Banbury; Emil J. Njor; Matthew Stewart; Pete Warden; Manjunath Kudlur; Nat Jeffries; Xenofon Fafoutis; Vijay Janapa Reddi (CoRR, 2024)

HESSO: Towards Automatic Efficient and User Friendly Any Neural Network Training and Pruning. - Tianyi Chen; Xiaoyi Qu; David Aponte; Colby R. Banbury; Jongwoo Ko; Tianyu Ding; Yong Ma; Vladimir Lyapunov; Ilya Zharkov; Luming Liang (CoRR, 2024)

Automatic Joint Structured Pruning and Quantization for Efficient Neural Network Training and Compression. - Xiaoyi Qu; David Aponte; Colby R. Banbury; Daniel P. Robinson; Tianyu Ding; Kazuhito Koishida; Ilya Zharkov; Tianyi Chen (CVPR, 2025)

Fast data aware neural architecture search via supernet accelerated evaluation. - Emil J. Njor; Colby R. Banbury; Xenofon Fafoutis (Internet Things, 2025)

WinClick: GUI Grounding with Multimodal Large Language Models. - Zheng Hui; Yinheng Li; Dan Zhao; Tianyi Chen; Colby R. Banbury; Kazuhito Koishida (CoRR, 2025)

WINA: Weight Informed Neuron Activation for Accelerating Large Language Model Inference. - Sihan Chen; Dan Zhao; Jongwoo Ko; Colby R. Banbury; Huiping Zhuang; Luming Liang; Tianyi Chen (CoRR, 2025)