105 citations · 115 across the 7 of their papers we have counts for
7 papers
Rate-Regularization and Generalization in VAEs
Alican Bozkurt, Babak Esmaeili, Jean-Baptiste Tristan +3
Variational autoencoders optimize an objective that combines a reconstruction loss (the distortion) and a KL term (the rate). The rate is an upper bound on the mutual information,…
Can VAEs Generate Novel Examples?
Alican Bozkurt, Babak Esmaeili, Dana H. Brooks +2
An implicit goal in works on deep generative models is that such models should be able to generate novel examples that were not previously seen in the training data. In this paper,…
Structured Disentangled Representations
Babak Esmaeili, Hao Wu, Sarthak Jain +6
Deep latent-variable models learn representations of high-dimensional data in an unsupervised manner. A number of recent efforts have focused on learning representations that disen…
Classifying Fonts and Calligraphy Styles Using Complex Wavelet Transform
Alican Bozkurt, Pinar Duygulu, A. Enis Cetin
Recognizing fonts has become an important task in document analysis, due to the increasing number of available digital documents in different fonts and emphases. A generic font-rec…
Deconvolution Using Projections Onto The Epigraph Set of a Convex Cost Function
Mohammad Tofighi, Alican Bozkurt, A. Enis Cetin
A new deconvolution algorithm based on orthogonal projections onto the epigraph set of a convex cost function is presented. In this algorithm, the dimension of the minimization pro…
Approximate Computation of DFT without Performing Any Multiplications: Applications to Radar Signal Processing
Alican Bozkurt, Musa Tunç Arslan, Rasim Akin Sevimli +2
In many practical problems it is not necessary to compute the DFT in a perfect manner including some radar problems. In this article a new multiplication free algorithm for approxi…
Projections Onto Convex Sets (POCS) Based Optimization by Lifting
A. Enis Cetin, Alican Bozkurt, Osman Gunay +4
Two new optimization techniques based on projections onto convex space (POCS) framework for solving convex and some non-convex optimization problems are presented. The dimension of…