Self-compressing neural networks
The last decade of AI research has been characterised by the exploration of the potential of deep neural networks. The advances we have seen in recent.
Szabolcs Csefalvay
October 10, 2022
High-Fidelity Conversion of Floating-Point Networks for Low-Precision Inference using Distillation
A major challenge for fast, low-power inference on neural network accelerators is the size of the models. There is a trend in recent years towards deeper.
Szabolcs Csefalvay
May 25, 2021
