Compiling KB-sized machine learning models to tiny IoT devices. - Sridhar Gopinath; Nikhil Ghanathe; Vivek Seshadri; Rahul Sharma 001 (PLDI, 2019)

MAFIA: Machine Learning Acceleration on FPGAs for IoT Applications. - Nikhil Pratap Ghanathe; Vivek Seshadri; Rahul Sharma 001; Steve Wilton; Aayan Kumar (FPL, 2021)

T-RecX: Tiny-Resource Efficient Convolutional neural networks with early-eXit. - Nikhil Pratap Ghanathe; Steve Wilton (CF, 2023)

Enabling Risk Management of Machine Learning Predictions for FPGA Routability. - Andrew David Gunter; Maya Thomas; Nikhil Pratap Ghanathe; Steven J. E. Wilton (MLCAD, 2024)

QUTE: Quantifying Uncertainty in TinyML models with Early-exit-assisted ensembles. - Nikhil Pratap Ghanathe; Steve Wilton (CoRR, 2024)

DEBUG-HD: Debugging TinyML models on-device using Hyper-Dimensional computing. - Nikhil Pratap Ghanathe; Steven J. E. Wilton (CoRR, 2024)