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Found 3 papers, 2 papers with code
GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction
Graph Anomaly Detection (GAD) is a technique used to identify abnormal nodes within graphs, finding applications in network security, fraud detection, social media spam detection, and various other domains.
Contrastive Cycle Adversarial Autoencoders for Single-cell Multi-omics Alignment and Integration
Our approach can efficiently map the above data with high sparsity and noise from different spaces to a low-dimensional manifold in a unified space, making the downstream alignment and integration straightforward.
Understanding Adversarial Examples Through Deep Neural Network's Response Surface and Uncertainty Regions
Our study reveals the structural problem of DNN classification boundary that leads to the adversarial examples.
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