Quantization-Guided Training for Compact TinyML Models

10 March 2021

Papers citing "Quantization-Guided Training for Compact TinyML Models"

6 / 6 papers shown

Title
Quantizing Small-Scale State-Space Models for Edge AI Leo Zhao Tristan Torchet Melika Payvand Laura Kriener Filippo Moro MQ 94 2 0 14 Jun 2025
Deep learning model compression using network sensitivity and gradients M. Sakthi N. Yadla Raj Pawate 82 2 0 11 Oct 2022
Overcoming Oscillations in Quantization-Aware Training Markus Nagel Marios Fournarakis Yelysei Bondarenko Tijmen Blankevoort MQ 273 125 0 21 Mar 2022
An Empirical Study of Low Precision Quantization for TinyML Shaojie Zhuo Hongyu Chen R. Ramakrishnan Tommy Chen Chen Feng Yi-Rung Lin Parker Zhang Liang Shen MQ 179 18 0 10 Mar 2022
Implicit Neural Representations for Image Compression Yannick Strümpler Janis Postels Ren Yang Luc van Gool F. Tombari 179 176 0 08 Dec 2021
A TinyML Platform for On-Device Continual Learning with Quantized Latent Replays Leonardo Ravaglia Manuele Rusci D. Nadalini Alessandro Capotondi Francesco Conti Luca Benini BDL 144 77 0 20 Oct 2021