Tensor completion is a fundamental tool for incomplete data analysis, where the goal is to predict missing entries from partial observations. However, existing methods often make the explicit or ...

Low-rank tensor completion aims to recover the missing entries of multi-way data, which has become popular and vital in many fields such as signal processing and computer vision. It varies with ...

TensorFlow Image Models (tfimm) is a collection of image models with pretrained weights, obtained by porting architectures from timm to TensorFlow. The hope is that the number of available ...