3 papers
cs.LG2019
Composition and decomposition of GANs
Yeu-Chern Harn, Zhenghao Chen, Vladimir Jojic
In this work, we propose a composition/decomposition framework for adversarially training generative models on composed data - data where each sample can be thought of as being con…
cs.LG2016
Degrees of Freedom in Deep Neural Networks
Tianxiang Gao, Vladimir Jojic
In this paper, we explore degrees of freedom in deep sigmoidal neural networks. We show that the degrees of freedom in these models is related to the expected optimism, which is th…
q-bio.GN2012
Joint discovery of haplotype blocks and complex trait associations from SNP sequences
Nebojsa Jojic, Vladimir Jojic, David Heckerman
Haplotypes, the global patterns of DNA sequence variation, have important implications for identifying complex traits. Recently, blocks of limited haplotype diversity have been dis…