166 citations · 174 across the 6 of their papers we have counts for
6 papers
MetaboNet-Bench: A Multi-modal Benchmark for Glucose Forecasting in Type 1 Diabetes
Nathaniel Jeffries, Miriam Wolff, Sam Royston +5
Glucose forecasting algorithms are an important aspect of glycemic control management in type 1 diabetes. So far, the research community has developed numerous algorithms and model…
Moonshine: Speech Recognition for Live Transcription and Voice Commands
Nat Jeffries, Evan King, Manjunath Kudlur +3
This paper introduces Moonshine, a family of speech recognition models optimized for live transcription and voice command processing. Moonshine is based on an encoder-decoder trans…
Wake Vision: A Tailored Dataset and Benchmark Suite for TinyML Computer Vision Applications
Colby Banbury, Emil Njor, Andrea Mattia Garavagno +7
Tiny machine learning (TinyML) co-locates models with sensors on microcontrollers, where small models (which are disproportionately sensitive to label noise) and bespoke binary tas…
Datasheets for Machine Learning Sensors
Matthew Stewart, Yuke Zhang, Pete Warden +12
Machine learning (ML) is becoming prevalent in embedded AI sensing systems. These "ML sensors" enable context-sensitive, real-time data collection and decision-making across divers…
MLPerf Tiny Benchmark
Colby Banbury, Vijay Janapa Reddi, Peter Torelli +19
Advancements in ultra-low-power tiny machine learning (TinyML) systems promise to unlock an entirely new class of smart applications. However, continued progress is limited by the…
TensorFlow Lite Micro: Embedded Machine Learning on TinyML Systems
Robert David, Jared Duke, Advait Jain +10
Deep learning inference on embedded devices is a burgeoning field with myriad applications because tiny embedded devices are omnipresent. But we must overcome major challenges befo…