1 code implementation • 20 May 2020 • Benjamin Dutton
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.
1 code implementation • 20 Apr 2020 • Zexi Chen, Benjamin Dutton, Bharathkumar Ramachandra, Tianfu Wu, Ranga Raju Vatsavai
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.
no code implementations • 18 Jun 2019 • Bharathkumar Ramachandra, Benjamin Dutton, Ranga Raju Vatsavai
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.