Researchers have introduced the State Space Duality (SSD) framework, which connects Structured State Space Models (SSMs) and attention mechanisms, to improve the efficiency and…
Browsing: Attention Mechanisms
The article discusses the use of transformer-based models in solving combinatorial optimization problems, specifically the Traveling Salesman Problem (TSP). The Transformer, originally designed for…
Orchid is a new sequence modeling architecture that integrates a data-dependent convolution mechanism to overcome the limitations of traditional attention-based models. It aims to…
This book provides a comprehensive guide to deep learning, covering the basics of neural networks, convolutional networks for computer vision, and attention mechanisms and…
Transformers are a groundbreaking architecture in the field of natural language processing (NLP) that have revolutionized how machines understand and generate human language. This…
This Special Issue provides an overview of the recent advancements and emerging trends in deep learning for object detection. Deep-learning-based approaches have demonstrated significant…
This paper presents IKGM, a method based on deep learning with attention mechanisms for identifying key genes in the macroevolution of biological taxa. Using…
AI has come a long way since its inception in the 1950s and 1960s, with deep learning models like ChatGPT revolutionizing natural language processing.…
Google has unveiled a series of free short courses on generative AI, which is expected to reach a market size of $109.3 billion by…
Seedify, a leading launchpad and incubator in the crypto industry, has announced the launch of ChainGPT, an AI model designed to provide solutions and…