Towards spike-based machine intelligence with neuromorphic computing
Guided by brain-like 'spiking'computational frameworks, neuromorphic computing—brain-
inspired computing for machine intelligence—promises to realize artificial intelligence while …
inspired computing for machine intelligence—promises to realize artificial intelligence while …
Eligibility traces and plasticity on behavioral time scales: experimental support of neohebbian three-factor learning rules
Most elementary behaviors such as moving the arm to grasp an object or walking into the
next room to explore a museum evolve on the time scale of seconds; in contrast, neuronal …
next room to explore a museum evolve on the time scale of seconds; in contrast, neuronal …
Spikingjelly: An open-source machine learning infrastructure platform for spike-based intelligence
Spiking neural networks (SNNs) aim to realize brain-inspired intelligence on neuromorphic
chips with high energy efficiency by introducing neural dynamics and spike properties. As …
chips with high energy efficiency by introducing neural dynamics and spike properties. As …
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 …
Temporal coding in spiking neural networks with alpha synaptic function
We propose a spiking neural network model that encodes information in the relative timing
of individual neuron spikes and performs classification using the first output neuron to spike …
of individual neuron spikes and performs classification using the first output neuron to spike …
[图书][B] Neuronal dynamics: From single neurons to networks and models of cognition
What happens in our brain when we make a decision? What triggers a neuron to send out a
signal? What is the neural code? This textbook for advanced undergraduate and beginning …
signal? What is the neural code? This textbook for advanced undergraduate and beginning …
Bindsnet: A machine learning-oriented spiking neural networks library in python
The development of spiking neural network simulation software is a critical component
enabling the modeling of neural systems and the development of biologically inspired …
enabling the modeling of neural systems and the development of biologically inspired …
Spiking neural networks hardware implementations and challenges: A survey
M Bouvier, A Valentian, T Mesquida… - ACM Journal on …, 2019 - dl.acm.org
Neuromorphic computing is henceforth a major research field for both academic and
industrial actors. As opposed to Von Neumann machines, brain-inspired processors aim at …
industrial actors. As opposed to Von Neumann machines, brain-inspired processors aim at …
The building blocks of a brain-inspired computer
JD Kendall, S Kumar - Applied Physics Reviews, 2020 - pubs.aip.org
Computers have undergone tremendous improvements in performance over the last 60
years, but those improvements have significantly slowed down over the last decade, owing …
years, but those improvements have significantly slowed down over the last decade, owing …
A Reconfigurable Two‐WSe2‐Transistor Synaptic Cell for Reinforcement Learning
Reward‐modulated spike‐timing‐dependent plasticity (R‐STDP) is a brain‐inspired
reinforcement learning (RL) rule, exhibiting potential for decision‐making tasks and artificial …
reinforcement learning (RL) rule, exhibiting potential for decision‐making tasks and artificial …