Alternatively, if you would like to get an individual graph for each algorithm, some more specific simulations can be run with the `-advanced` flag. This will decode 2000 codewords at the variance ...

Marques in the master branch. In addition, the branch CAMSAP includes the experiments shown in a previous version of this work "An underparametrized deep decoder architecture for graph signals" by ...

In this paper, a method of knowledge reasoning and completion based on neural networks on the knowledge graph is designed for robots to simulate the reaction and learning process of human brains. Our ...

However, the conventional deep neural network decoder (DNND)usually suffers the computational mismatch and the lack of generalization capability. In this paper, we propose a novel Graph-Neural-Network ...

The team introduced a method called "Plan Like a Graph" (PLaG) in a recent paper.c PLaG works with all language models tested, improving their performance. It's ready to use now and compatible with ...

Abstract: Vision-based action segmentation is an important tool in human movement analysis. In this work, we present a novel Encoder-Decoder Graph Convolutional Network (ED-GCN) to perform ...