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GANSpace: Discovering Interpretable GAN Controls
This paper describes a simple technique to analyze Generative Adversarial Networks (GANs) and create interpretable controls for image synthesis.
generative-adversarial-networks image-generation interpretability interpretable-gans
A deep generative model for dimensionality reduction and clustering.
dimensionality-reduction clustering autoencoders variational-autoencoders
Machine Learning for Humans, Part 3: Unsupervised Learning
Clustering and dimensionality reduction: k-means clustering, hierarchical clustering, principal component analysis (PCA), singular value decomposition ...
unsupervised-learning clustering dimensionality-reduction principal-component-analysis
The Beginner's Guide to Dimensionality Reduction
Explore the methods that data scientists use to visualize high-dimensional data.
dimensionality-reduction interactive principal-component-analysis tsne
Fast Fourier Transform-accelerated Interpolation-based t-SNE (FIt-SNE).
dimensionality-reduction tsne fast-fourier-transform library
Differential Subspace Search in High-Dimensional Latent Space
Differential subspace search to allow efficient iterative user exploration in such a space, without relying on domain- or data-specific assumptions.
generative-models dimensionality-reduction singular-value-decompoition latent-space
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