178 citations · 189 across the 3 of their papers we have counts for
3 papers
Learning and Inference in Sparse Coding Models with Langevin Dynamics
Michael Y. -S. Fang, Mayur Mudigonda, Ryan Zarcone +2
We describe a stochastic, dynamical system capable of inference and learning in a probabilistic latent variable model. The most challenging problem in such models - sampling the po…
Design of optical neural networks with component imprecisions
Michael Y. -S. Fang, Sasikanth Manipatruni, Casimir Wierzynski +2
For the benefit of designing scalable, fault resistant optical neural networks (ONNs), we investigate the effects architectural designs have on the ONNs' robustness to imprecise co…
3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation
Magdalini Paschali, Stefano Gasperini, Abhijit Guha Roy +2
Model architectures have been dramatically increasing in size, improving performance at the cost of resource requirements. In this paper we propose 3DQ, a ternary quantization meth…