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Found 5 papers, 2 papers with code
Yet Meta Learning Can Adapt Fast, It Can Also Break Easily
Thus, in this paper, we perform the initial study about adversarial attacks on meta learning under the few-shot classification problem.
DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses
DeepRobust is a PyTorch adversarial learning library which aims to build a comprehensive and easy-to-use platform to foster this research field.
Adversarial Attacks and Defenses on Graphs: A Review, A Tool and Empirical Studies
As the extensions of DNNs to graphs, Graph Neural Networks (GNNs) have been demonstrated to inherit this vulnerability.
Multi-wavelet residual dense convolutional neural network for image denoising
Networks with large receptive field (RF) have shown advanced fitting ability in recent years.
Automatic marker-free registration of tree point-cloud data based on rotating projection
In coarse registration, point clouds produced by each scan are projected onto a spherical surface to generate a series of two-dimensional (2D) images, which are used to estimate the initial positions of multiple scans.
