In this paper, we propose a GAT (graph attention network)-based deep reinforcement learning (DRL) algorithm to solve task scheduling problems. This method combines the benefits of deep learning (DL) ...

We present DySample, an ultra-lightweight and effective dynamic upsampler. While impressive performance gains have been witnessed from recent kernel-based dynamic upsamplers such as CARAFE, FADE, and ...