A TinyML Platform for On-Device Continual Learning With Quantized Latent Replays. - Leonardo Ravaglia; Manuele Rusci; Davide Nadalini; Alessandro Capotondi; Francesco Conti 001; Luca Benini (IEEE J. Emerg. Sel. Topics Circuits Syst., 2021)

PULP-TrainLib: Enabling On-Device Training for RISC-V Multi-core MCUs Through Performance-Driven Autotuning. - Davide Nadalini; Manuele Rusci; Giuseppe Tagliavini; Leonardo Ravaglia; Luca Benini; Francesco Conti 001 (SAMOS, 2022)

Reduced precision floating-point optimization for Deep Neural Network On-Device Learning on microcontrollers. - Davide Nadalini; Manuele Rusci; Luca Benini; Francesco Conti 001 (Future Gener. Comput. Syst., 2023)

Structured Sparse Back-propagation for Lightweight On-Device Continual Learning on Microcontroller Units. - Francesco Paissan; Davide Nadalini; Manuele Rusci; Alberto Ancilotto; Francesco Conti 001; Luca Benini; Elisabetta Farella (CVPR Workshops, 2024)

Compressed Latent Replays for Lightweight Continual Learning on Spiking Neural Networks. - Alberto Dequino; Alessio Carpegna; Davide Nadalini; Alessandro Savino; Luca Benini; Stefano Di Carlo; Francesco Conti 001 (ISVLSI, 2024)