2.1k citations · 2.4k across the 35 of their papers we have counts for
4 papers · 2 filters
PT-MMD: A Novel Statistical Framework for the Evaluation of Generative Systems
Alexander Potapov, Ian Colbert, Ken Kreutz-Delgado +2
Stochastic-sampling-based Generative Neural Networks, such as Restricted Boltzmann Machines and Generative Adversarial Networks, are now used for applications such as denoising, im…
Coresets for Estimating Means and Mean Square Error with Limited Greedy Samples
Saeed Vahidian, Baharan Mirzasoleiman, Alexander Cloninger
In a number of situations, collecting a function value for every data point may be prohibitively expensive, and random sampling ignores any structure in the underlying data. We int…
Variational Diffusion Autoencoders with Random Walk Sampling
Henry Li, Ofir Lindenbaum, Xiuyuan Cheng +1
Variational autoencoders (VAEs) and generative adversarial networks (GANs) enjoy an intuitive connection to manifold learning: in training the decoder/generator is optimized to app…
A witness function based construction of discriminative models using Hermite polynomials
H. N. Mhaskar, A. Cloninger, X. Cheng
In machine learning, we are given a dataset of the form , drawn as i.i.d. samples from an unknown probability distribution ; the marginal distrib…