Search
Search Results
-
Residual Graph Convolution Collaborative Filtering with Asymmetric neighborhood aggregation
Due to the superior performance of graph convolutional networks (GCNs) in feature extraction and representation, researchers have introduced GCNs to...
-
NV2P-RCNN: Feature Aggregation Based on Voxel Neighborhood for 3D Object Detection
In this paper, we propose a two-stage framework based on voxel neighborhood feature aggregation for 3D object detection in autonomous driving, named...
-
NE-WNA: A Novel Network Embedding Framework Without Neighborhood Aggregation
Graph Neural Networks (GNNs) are powerful tools in representation learning for graphs. Most GNNs use the message passing mechanism to obtain a...
-
BotRGA: Neighborhood-Aware Twitter Bot Detection with Relational Graph Aggregation
With the rapid development of AI-based technology, social bot detection is becoming an increasingly challenging task to combat the spread of...
-
Macsum Aggregation Learning and Missing Values
In recent work, a new kind of aggregation method has been proposed under the name of MacSum aggregation function that can be viewed as an interval...
-
ANGraph: attribute-interactive neighborhood-aggregative graph representation learning
We study the graph representation learning problem that has emerged with the advent of numerous graph analysis tasks in the recent past. The task of...
-
Order structure analysis of node importance based on the temporal inter-layer neighborhood homogeneity rate of the dynamic network
The analysis of node order structure in dynamic temporal networks is significant for network propagation control. To further accurately characterize...
-
WalkNAR: A neighborhood rough sets-based attribute reduction approach using random walk
Neighborhood rough sets, as an effective tool for processing numerical data, is widely used in many fields, such as data mining, machine learning and...
-
Weakly supervised semantic segmentation with segments and neighborhood classifiers
Semantic segmentation can provide basic semantic information for scene understanding, which has important theoretical research value and broad...
-
Graph Convolutional Network Based on Higher-Order Neighborhood Aggregation
The graph neural network can use the network topology, the attributes and labels of nodes to mine the potential relationships on network. In paper,...
-
Decomposition-based multiobjective evolutionary algorithm with density estimation-based dynamical neighborhood strategy
The multiobjective evolutionary algorithm based on decomposition (MOEA/D) decomposes a multiobjective optimization problem (MOP) into several scalar...
-
Relational metric learning with high-order neighborhood interactions for social recommendation
Social information has been widely incorporated into traditional recommendation systems to alleviate the data sparsity and cold-start issues....
-
Global Entity Alignment with Gated Latent Space Neighborhood Aggregation
Existing entity alignment models mainly use the topology structure of the original knowledge graph and have achieved promising performance. However,...
-
Low-rank GAT: toward robust quantification of neighborhood influence
Graph attention networks stack self-attention layers to compute the neighbor-specific weights. Due to inherent noise and artificially correlated...
-
Neighborhood-enhanced contrast for pre-training graph neural networks
Pre-training graph neural networks (GNNs) have been proposed to promote graph-related downstream tasks, such as link prediction and node...
-
Semantic segmentation of large-scale point clouds with neighborhood uncertainty
Large-scale point cloud segmentation is one of the important research directions in the field of computer vision, aiming at segmenting 3D point cloud...
-
A Novel Neighborhood-Augmented Graph Attention Network for Sequential Recommendation
In recent years, sequential recommender systems have been widely applied for alleviating information overload. Some solutions employ graph attention...
-
Robust point cloud normal estimation via multi-level critical point aggregation
We propose a multi-level critical point aggregation architecture based on a graph attention mechanism for 3D point cloud normal estimation, which can...
-
Guided aggregation and disparity refinement for real-time stereo matching
Stereo matching methods based on convolution neural network (CNN) often face challenges such as edge blurring and the loss of small structures. These...
-
Robust depth completion based on Semantic Aggregation
AbstractGuided by information from RGB images, depth completion methods rebuild the dense depth from sparse depth input. However, the varying...
