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Found 5 papers, 3 papers with code
Deep recurrent Gaussian process with variational Sparse Spectrum approximation
In this paper we introduce several new Deep recurrent Gaussian process (DRGP) models based on the Sparse Spectrum Gaussian process (SSGP) and the improved version, called variational Sparse Spectrum Gaussian process (VSSGP).
CANet: An Unsupervised Intrusion Detection System for High Dimensional CAN Bus Data
For reproducibility of the method, our synthetic data is publicly available.
Unpaired High-Resolution and Scalable Style Transfer Using Generative Adversarial Networks
Neural networks have proven their capabilities by outperforming many other approaches on regression or classification tasks on various kinds of data.
Deep Recurrent Gaussian Process with Variational Sparse Spectrum Approximation
Modeling sequential data has become more and more important in practice.
Ensemble Methods as a Defense to Adversarial Perturbations Against Deep Neural Networks
We propose to use ensemble methods as a defense strategy against adversarial perturbations.
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