Opportunities for neuromorphic computing algorithms and applications
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 …
much of the work in neuromorphic computing has focused on hardware development. Here …
The future of memristors: Materials engineering and neural networks
K Sun, J Chen, X Yan - Advanced Functional Materials, 2021 - Wiley Online Library
Abstract From Deep Blue to AlphaGo, artificial intelligence and machine learning are
booming, and neural networks have become the hot research direction. However, due to the …
booming, and neural networks have become the hot research direction. However, due to the …
Over and above frequency: Gamma oscillations as units of neural circuit operations
Summary Gamma oscillations (∼ 30–150 Hz) are widespread correlates of neural circuit
functions. These network activity patterns have been described across multiple animal …
functions. These network activity patterns have been described across multiple animal …
Loihi: A neuromorphic manycore processor with on-chip learning
Loihi is a 60-mm2 chip fabricated in Intels 14-nm process that advances the state-of-the-art
modeling of spiking neural networks in silicon. It integrates a wide range of novel features for …
modeling of spiking neural networks in silicon. It integrates a wide range of novel features for …
A review of learning in biologically plausible spiking neural networks
Artificial neural networks have been used as a powerful processing tool in various areas
such as pattern recognition, control, robotics, and bioinformatics. Their wide applicability has …
such as pattern recognition, control, robotics, and bioinformatics. Their wide applicability has …
[HTML][HTML] Toward an integration of deep learning and neuroscience
AH Marblestone, G Wayne, KP Kording - Frontiers in computational …, 2016 - frontiersin.org
Neuroscience has focused on the detailed implementation of computation, studying neural
codes, dynamics and circuits. In machine learning, however, artificial neural networks tend …
codes, dynamics and circuits. In machine learning, however, artificial neural networks tend …
Spiking neural networks and online learning: An overview and perspectives
Applications that generate huge amounts of data in the form of fast streams are becoming
increasingly prevalent, being therefore necessary to learn in an online manner. These …
increasingly prevalent, being therefore necessary to learn in an online manner. These …
[HTML][HTML] Coupled oscillators for computing: A review and perspective
Coupled oscillators are highly complex dynamical systems, and it is an intriguing concept to
use this oscillator dynamics for computation. The idea is not new, but is currently the subject …
use this oscillator dynamics for computation. The idea is not new, but is currently the subject …
Silicon photonic modulator neuron
There has been recent interest in neuromorphic photonics, a field with the promise to access
pivotal and unexplored regimes of machine intelligence. Progress has been made on …
pivotal and unexplored regimes of machine intelligence. Progress has been made on …
Broadcast and weight: an integrated network for scalable photonic spike processing
We propose an on-chip optical architecture to support massive parallel communication
among high-performance spiking laser neurons. Designs for a network protocol …
among high-performance spiking laser neurons. Designs for a network protocol …