Zobrazeno 1 - 10
of 1 858
pro vyhledávání: '"Logan, G. A."'
Autor:
Momeni, Ali, Rahmani, Babak, Scellier, Benjamin, Wright, Logan G., McMahon, Peter L., Wanjura, Clara C., Li, Yuhang, Skalli, Anas, Berloff, Natalia G., Onodera, Tatsuhiro, Oguz, Ilker, Morichetti, Francesco, del Hougne, Philipp, Gallo, Manuel Le, Sebastian, Abu, Mirhoseini, Azalia, Zhang, Cheng, Marković, Danijela, Brunner, Daniel, Moser, Christophe, Gigan, Sylvain, Marquardt, Florian, Ozcan, Aydogan, Grollier, Julie, Liu, Andrea J., Psaltis, Demetri, Alù, Andrea, Fleury, Romain
Physical neural networks (PNNs) are a class of neural-like networks that leverage the properties of physical systems to perform computation. While PNNs are so far a niche research area with small-scale laboratory demonstrations, they are arguably one
Externí odkaz:
http://arxiv.org/abs/2406.03372
Autor:
Onodera, Tatsuhiro, Stein, Martin M., Ash, Benjamin A., Sohoni, Mandar M., Bosch, Melissa, Yanagimoto, Ryotatsu, Jankowski, Marc, McKenna, Timothy P., Wang, Tianyu, Shvets, Gennady, Shcherbakov, Maxim R., Wright, Logan G., McMahon, Peter L.
On-chip photonic processors for neural networks have potential benefits in both speed and energy efficiency but have not yet reached the scale at which they can outperform electronic processors. The dominant paradigm for designing on-chip photonics i
Externí odkaz:
http://arxiv.org/abs/2402.17750
Autor:
Presutti, Federico, Wright, Logan G., Ma, Shi-Yuan, Wang, Tianyu, Malia, Benjamin K., Onodera, Tatsuhiro, McMahon, Peter L.
Multimode squeezed states of light have been proposed as a resource for achieving quantum advantage in computing and sensing. Recent experiments that demonstrate multimode Gaussian states to this end have most commonly opted for spatial or temporal m
Externí odkaz:
http://arxiv.org/abs/2401.06119
Autor:
Senanian, Alen, Prabhu, Sridhar, Kremenetski, Vladimir, Roy, Saswata, Cao, Yingkang, Kline, Jeremy, Onodera, Tatsuhiro, Wright, Logan G., Wu, Xiaodi, Fatemi, Valla, McMahon, Peter L.
Publikováno v:
Nature Communications 15, 7490 (2024)
Quantum reservoir computing (QRC) has been proposed as a paradigm for performing machine learning with quantum processors where the training is efficient in the number of required runs of the quantum processor and takes place in the classical domain,
Externí odkaz:
http://arxiv.org/abs/2312.16166
Autor:
Yanagimoto, Ryotatsu, Ng, Edwin, Jankowski, Marc, Nehra, Rajveer, McKenna, Timothy P., Onodera, Tatsuhiro, Wright, Logan G., Hamerly, Ryan, Marandi, Alireza, Fejer, M. M., Mabuchi, Hideo
Publikováno v:
Optica 11, 896(2024)
Over the last few decades, nonlinear optics has become significantly more nonlinear, traversing nearly a billionfold improvement in energy efficiency, with ultrafast nonlinear nanophotonics in particular emerging as a frontier for combining both spat
Externí odkaz:
http://arxiv.org/abs/2311.13775
Publikováno v:
Neuron 112 (2), 180-183, 2024
Human brains and bodies are not hardware running software: the hardware is the software. We reason that because the microscopic physics of artificial-intelligence hardware and of human biological "hardware" is distinct, neuromorphic engineers need to
Externí odkaz:
http://arxiv.org/abs/2310.18335
Analog physical neural networks, which hold promise for improved energy efficiency and speed compared to digital electronic neural networks, are nevertheless typically operated in a relatively high-power regime so that the signal-to-noise ratio (SNR)
Externí odkaz:
http://arxiv.org/abs/2307.15712
Autor:
Alen Senanian, Sridhar Prabhu, Vladimir Kremenetski, Saswata Roy, Yingkang Cao, Jeremy Kline, Tatsuhiro Onodera, Logan G. Wright, Xiaodi Wu, Valla Fatemi, Peter L. McMahon
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-9 (2024)
Abstract Quantum reservoir computing (QRC) has been proposed as a paradigm for performing machine learning with quantum processors where the training takes place in the classical domain, avoiding the issue of barren plateaus in parameterized-circuit
Externí odkaz:
https://doaj.org/article/1f9ad954968f4210b6b235dca912ea81
Publikováno v:
Transactions on Machine Learning Research, 03/2024, https://openreview.net/forum?id=Xxw0edFFQC
The rapidly increasing size of deep-learning models has caused renewed and growing interest in alternatives to digital computers to dramatically reduce the energy cost of running state-of-the-art neural networks. Optical matrix-vector multipliers are
Externí odkaz:
http://arxiv.org/abs/2302.10360
Autor:
Logan G. Mills, Barbara Newsom, Abigail Lewis, Alexandra Pottorff, Ashley Wallace Wu, Erika Castro, Kelsi Morgan, Lawrence Wu, Bau P. Tran, Katherine Lake, Mina Guirguis, James M. Wagner, Nora Gimpel, Tiffany B. Kindratt
Publikováno v:
Journal of Primary Care & Community Health, Vol 15 (2024)
Introduction/Objectives: The cost of medical services is a major barrier to healthcare accessibility for underserved populations in the United States. Community charity medical clinics help address this disparity by providing free or reduced-cost car
Externí odkaz:
https://doaj.org/article/13968e25f2bd42e1905f773afb8ac658