316 citations · 668 across the 5 of their papers we have counts for
6 papers
Efficient Optimization with Higher-Order Ising Machines
Connor Bybee, Denis Kleyko, Dmitri E. Nikonov +3
A prominent approach to solving combinatorial optimization problems on parallel hardware is Ising machines, i.e., hardware implementations of networks of interacting binary spin va…
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…
Integer Factorization with Compositional Distributed Representations
Denis Kleyko, Connor Bybee, Christopher J. Kymn +5
In this paper, we present an approach to integer factorization using distributed representations formed with Vector Symbolic Architectures. The approach formulates integer factoriz…
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…
Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks
Urs Köster, Tristan J. Webb, Xin Wang +11
Deep neural networks are commonly developed and trained in 32-bit floating point format. Significant gains in performance and energy efficiency could be realized by training and in…
Application of Deep Convolutional Neural Networks for Detecting Extreme Weather in Climate Datasets
Yunjie Liu, Evan Racah, Prabhat +6
Detecting extreme events in large datasets is a major challenge in climate science research. Current algorithms for extreme event detection are build upon human expertise in defini…