Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Khosrowshahi Amir"'
Autor:
Bybee, Connor, Kleyko, Denis, Nikonov, Dmitri E., Khosrowshahi, Amir, Olshausen, Bruno A., Sommer, Friedrich T.
A prominent approach to solving combinatorial optimization problems on parallel hardware is Ising machines, i.e., hardware implementations of networks of interacting binary spin variables. Most Ising machines leverage second-order interactions althou
Externí odkaz:
http://arxiv.org/abs/2212.03426
Autor:
Fang, Michael Y. -S., Mudigonda, Mayur, Zarcone, Ryan, Khosrowshahi, Amir, Olshausen, Bruno A.
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 posterior distribution over latent variables - is proposed to be solved
Externí odkaz:
http://arxiv.org/abs/2204.11150
Autor:
Kleyko, Denis, Bybee, Connor, Kymn, Christopher J., Olshausen, Bruno A., Khosrowshahi, Amir, Nikonov, Dmitri E., Sommer, Friedrich T., Frady, E. Paxon
Publikováno v:
NICE 2022: Neuro-Inspired Computational Elements Conference
In this paper, we present an approach to integer factorization using distributed representations formed with Vector Symbolic Architectures. The approach formulates integer factorization in a manner such that it can be solved using neural networks and
Externí odkaz:
http://arxiv.org/abs/2203.00920
Publikováno v:
BMC Neuroscience, Vol 13, Iss Suppl 1, p P143 (2012)
Externí odkaz:
https://doaj.org/article/d8a15493ceac45aea98d1c5650615b68
Publikováno v:
In Journal of Materials Research and Technology March-April 2024 29:3279-3290
Autor:
Fang, Michael Y. -S., Manipatruni, Sasikanth, Wierzynski, Casimir, Khosrowshahi, Amir, DeWeese, Michael R.
Publikováno v:
Optics express 27.10 (2019): 14009-14029
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 components. We train two ONNs -- one with a more tunable design (GridNet
Externí odkaz:
http://arxiv.org/abs/2001.01681
Publikováno v:
In Ceramics International 1 June 2022 48(11):16326-16336
Autor:
Köster, Urs, Webb, Tristan J., Wang, Xin, Nassar, Marcel, Bansal, Arjun K., Constable, William H., Elibol, Oğuz H., Gray, Scott, Hall, Stewart, Hornof, Luke, Khosrowshahi, Amir, Kloss, Carey, Pai, Ruby J., Rao, Naveen
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 inference in numerical formats optimized for deep learning. Despite adva
Externí odkaz:
http://arxiv.org/abs/1711.02213
Autor:
Liu, Yunjie, Racah, Evan, Prabhat, Correa, Joaquin, Khosrowshahi, Amir, Lavers, David, Kunkel, Kenneth, Wehner, Michael, Collins, William
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 defining events based on subjective thresholds of relevant physical variable
Externí odkaz:
http://arxiv.org/abs/1605.01156
Autor:
Kahaie Khosrowshahi, Amir, Khoshfetrat, Ali Baradar *, Khosrowshahi, Younes Beygi, Maleki-Ghaleh, Hossein
Publikováno v:
In Materials Today Communications June 2021 27