Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

The conservative organization first announced its plans for a halftime show alternative following right-wing backlash to Puerto Rican superstar Bad Bunny. By Ethan Millman Music Editor “We’re ...

Abstract: Point cloud completion concerns the inference of the completed geometries for real-scanned point clouds that are sparse and incomplete due to occlusion, noise, and viewpoint. Previous ...

Abstract: Deep Neural Networks (DNNs) impose significant computational demands, necessitating optimizations for computational and energy efficiencies. Per-vector scaling, which applies a scaling ...

Abstract: Space-air-ground integrated networks (SAGINs) face unprecedented security challenges due to their inherent characteristics, such as multidimensional heterogeneity and dynamic topologies.

Abstract: Affective brain–computer interfaces (aBCIs) are an emerging technology that decodes brain signals—primarily electroencephalography (EEG)—to monitor and regulate emotional states in real time ...

To use MSG.exe to send a message to a network computer, you need the name or IP address of the target computer. Also, the destination computers should be connected to the same local network. Add ...

Abstract: Point cloud completion aims to infer complete point clouds based on partial 3D point cloud inputs. Various previous methods apply coarse-to-fine strategy networks for generating complete ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

Abstract: In point cloud, some regions typically exist nodes from multiple categories, i.e., these regions have both homophilic and heterophilic nodes. However, most existing methods ignore the ...

Abstract: This paper investigates a GraphRAG framework that integrates knowledge graphs into the Retrieval-Augmented Generation (RAG) architecture to enhance networking applications. While RAG has ...