384 citations · 650 across the 17 of their papers we have counts for
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cs.LG2019
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…
eess.IV2019
AX-DBN: An Approximate Computing Framework for the Design of Low-Power Discriminative Deep Belief Networks
Ian Colbert, Ken Kreutz-Delgado, Srinjoy Das
The power budget for embedded hardware implementations of Deep Learning algorithms can be extremely tight. To address implementation challenges in such domains, new design paradigm…