[HTML][HTML] Opportunities for neuromorphic computing algorithms and applications

CD Schuman, SR Kulkarni, M Parsa… - Nature Computational …, 2022 - nature.com
Neuromorphic computing technologies will be important for the future of computing, but
much of the work in neuromorphic computing has focused on hardware development. Here …

Applications of optical microcombs

Y Sun, J Wu, M Tan, X Xu, Y Li, R Morandotti… - Advances in Optics …, 2023 - opg.optica.org
Optical microcombs represent a new paradigm for generating laser frequency combs based
on compact chip-scale devices, which have underpinned many modern technological …

Biological underpinnings for lifelong learning machines

D Kudithipudi, M Aguilar-Simon, J Babb… - Nature Machine …, 2022 - nature.com
Biological organisms learn from interactions with their environment throughout their lifetime.
For artificial systems to successfully act and adapt in the real world, it is desirable to similarly …

A survey on federated learning for resource-constrained IoT devices

A Imteaj, U Thakker, S Wang, J Li… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Federated learning (FL) is a distributed machine learning strategy that generates a global
model by learning from multiple decentralized edge clients. FL enables on-device training …

Polariton condensates for classical and quantum computing

A Kavokin, TCH Liew, C Schneider… - Nature Reviews …, 2022 - nature.com
Polariton lasers emit coherent monochromatic light through a spontaneous emission
process. As a rare example of a system in which Bose–Einstein condensation and …

A survey on ChatGPT: AI-generated contents, challenges, and solutions

Y Wang, Y Pan, M Yan, Z Su… - IEEE Open Journal of the …, 2023 - ieeexplore.ieee.org
With the widespread use of large artificial intelligence (AI) models such as ChatGPT, AI-
generated content (AIGC) has garnered increasing attention and is leading a paradigm shift …

Neuromorphic spintronics

J Grollier, D Querlioz, KY Camsari… - Nature …, 2020 - nature.com
Neuromorphic computing uses brain-inspired principles to design circuits that can perform
computational tasks with superior power efficiency to conventional computers. Approaches …

Neuromorphic nanoelectronic materials

VK Sangwan, MC Hersam - Nature nanotechnology, 2020 - nature.com
Memristive and nanoionic devices have recently emerged as leading candidates for
neuromorphic computing architectures. While top-down fabrication based on conventional …

[HTML][HTML] A state-of-the-art survey on deep learning theory and architectures

MZ Alom, TM Taha, C Yakopcic, S Westberg, P Sidike… - electronics, 2019 - mdpi.com
In recent years, deep learning has garnered tremendous success in a variety of application
domains. This new field of machine learning has been growing rapidly and has been …

[PDF][PDF] Intelligent metaphotonics empowered by machine learning

S Krasikov, A Tranter, A Bogdanov… - Opto-Electronic …, 2022 - researching.cn
In the recent years, a dramatic boost of the research is observed at the junction of photonics,
machine learning and artificial intelligence. A new methodology can be applied to the …