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Found 3 papers, 2 papers with code
Adversarial Canonical Correlation Analysis
In this work, we explore straightforward adversarial alternatives to recent work in Deep Variational CCA (VCCA and VCCA-Private) we call ACCA and ACCA-Private and show how these approaches offer a stronger and more flexible way to match the approximate posteriors coming from encoders to much larger classes of priors than the VCCA and VCCA-Private models.
Local Clustering with Mean Teacher for Semi-supervised Learning
In MT, each data point is considered independent of other points during training; however, data points are likely to be close to each other in feature space if they share similar features.
Estimating a Manifold from a Tangent Bundle Learner
We formulate three methods that use the data assigned to each tangent space to estimate the underlying bounded subspaces for which the tangent space is a faithful estimate of the manifold and offer thoughts on how this perspective is theoretically grounded in the manifold assumption.
