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08/07/2023
Bridging Trustworthiness and Open-World Learning: An Exploratory Neural Approach for Enhancing Interpretability, Generalization, and Robustness
As researchers strive to narrow the gap between machine intelligence and...
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05/25/2023
High-Similarity-Pass Attention for Single Image Super-Resolution
Recent developments in the field of non-local attention (NLA) have led t...
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04/14/2023
AGNN: Alternating Graph-Regularized Neural Networks to Alleviate Over-Smoothing
Graph Convolutional Network (GCN) with the powerful capacity to explore ...
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04/13/2023
Attributed Multi-order Graph Convolutional Network for Heterogeneous Graphs
Heterogeneous graph neural networks aim to discover discriminative node ...
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04/03/2023
Properties and Potential Applications of Random Functional-Linked Types of Neural Networks
Random functional-linked types of neural networks (RFLNNs), e.g., the ex...
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02/05/2023
Deep Graph-Level Clustering Using Pseudo-Label-Guided Mutual Information Maximization Network
In this work, we study the problem of partitioning a set of graphs into ...
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12/09/2022
Multi-view Graph Convolutional Networks with Differentiable Node Selection
Multi-view data containing complementary and consensus information can f...
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12/05/2022
Refiner: Data Refining against Gradient Leakage Attacks in Federated Learning
Federated Learning (FL) is pervasive in privacy-focused IoT environments...
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11/16/2022
Learnable Graph Convolutional Network and Feature Fusion for Multi-view Learning
In practical applications, multi-view data depicting objectives from ass...
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09/14/2022
Federated Learning based on Defending Against Data Poisoning Attacks in IoT
The rapidly expanding number of Internet of Things (IoT) devices is gene...
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08/13/2022
MaskBlock: Transferable Adversarial Examples with Bayes Approach
The transferability of adversarial examples (AEs) across diverse models ...
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06/09/2022
Unsupervised Deep Discriminant Analysis Based Clustering
This work presents an unsupervised deep discriminant analysis for cluste...
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05/04/2022
Wasserstein Adversarial Learning based Temporal Knowledge Graph Embedding
Research on knowledge graph embedding (KGE) has emerged as an active fie...
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02/28/2022
Enhance transferability of adversarial examples with model architecture
Transferability of adversarial examples is of critical importance to lau...
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05/25/2021
The Component Diagnosability of General Networks
The processor failures in a multiprocessor system have a negative impact...
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07/18/2020
Object Tracking by Least Spatiotemporal Searches
Tracking a car or a person in a city is crucial for urban safety managem...
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07/03/2020
HDR-GAN: HDR Image Reconstruction from Multi-Exposed LDR Images with Large Motions
Synthesizing high dynamic range (HDR) images from multiple low-dynamic r...
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04/15/2020
Wasserstein Adversarial Autoencoders for Knowledge Graph Embedding based Drug-Drug Interaction Prediction
Interaction between pharmacological agents can trigger unexpected advers...
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11/26/2018
