In this paper, we tackle the high computational overhead of transformers for lightweight image super-resolution. (SR). Motivated by the observations of self-attention's inter-layer repetition, we ...

Abstract: Graph Convolution Networks (GCNs) have achieved remarkable success in representation of structured graph data. As we know that traditional GCNs are generally defined on the fixed first-order ...

Luke Littler’s World Darts Championship campaign was never meant to follow the script. No practice board. No hotel routine. And, by his own admission, a few “lazy” days on the sofa. Yet by the end of ...

Imagine Jo: Everyone in Jo's life recognizes her as an outstanding problem solver. She's the type of person who seems capable of almost anything. Jo excels at intuitive problem-solving. Over her life, ...

Abstract: Recently, some large kernel convnets strike back with appealing performance and efficiency. However, given the square complexity of convolution, scaling up kernels can bring about an ...

Artificial intelligence is consuming enormous amounts of energy, but researchers at the University of Florida have built a chip that could change everything by using light instead of electricity for a ...