Issues in Neural Network ResearchELSEVIERIntroduction to Neural Networks (Second Edition)
Most laypeople think of neural networks as a sort of artificial brain. Neural networks would be used to power robots or carry on intelligent conversations with human beings. This notion is a closer definition of Artificial Intelligence (AI), than neural networks. AI seeks to create truly intellig...
As discussed in the Introduction to this paper; one could argue that the discipline of soft or natural computing began with the development of Artificial Neural Networks (ANNs). The original motivations for the research were mainly: (a) a wish to shed light on the actual learning and computing...
Decision Theory: An Introduction to Dynamic Programming and Sequential Decisions Decision Theory An Introduction to Dynamic Programming and Sequential Decisions John Bather University of Sussex, UK Mathematical induction, and its use in... J Bather 被引量: 130发表: 2000年 A hybrid optimization approach...
Graph Neural Networks (GNNs) are widely used on a variety of graph-based machine learning tasks. For node-level tasks, GNNs are strong at modeling the homophily property of graphs (i.e., connected nodes are more similar), but their ability to capture the heterophily property is often doubt...
Introduction Neuroscience is a multidisciplinary field involving the study of the structure and function of the nervous system. The purpose is to understand the development of cognitive and behavioral processes as well as understand and find therapies for disorders, such as Alzheimer’s or Parkinson’...
introduction-neural-3d-reconstruction Course materials for Introduction to Neural 3D Reconstruction invis invisible megengine API juicefs-python JuiceFS Python SDK mdistiller The official implementation of [CVPR2022] Decoupled Knowledge Distillationhttps://arxiv.org/abs/2203.08679 ...
Introduction to Graph Neural Networks NVIDIA CV-CUDA NVIDIA introduced CV-CUDA, a new open source project enabling developers to build highly efficient, GPU-accelerated pre– and post-processing pipelines in cloud-scaleartificial intelligence (AI) imaging and computer vision (CV)workloads. ...
1. Introduction A knowledge graph [1] is essentially a structured semantic knowledge database that uses triples to describe the concepts, entities and their relations in the objective world. Specifically, the triples are represented in the form of (entity, relation and entity) or (entity, attribu...
slope safety factor; sparrow search algorithm; BP neural network; neural network optimization 1. Introduction In recent years, with the increasing economic development and urbanization around the world, landslides have become one of the main types of geological hazards that cause huge economic losses ...