[HTML][HTML] Brain-inspired learning in artificial neural networks: a review
Artificial neural networks (ANNs) have emerged as an essential tool in machine learning,
achieving remarkable success across diverse domains, including image and speech …
achieving remarkable success across diverse domains, including image and speech …
Spike-based local synaptic plasticity: A survey of computational models and neuromorphic circuits
Understanding how biological neural networks carry out learning using spike-based local
plasticity mechanisms can lead to the development of real-time, energy-efficient, and …
plasticity mechanisms can lead to the development of real-time, energy-efficient, and …
Meta-SpikePropamine: learning to learn with synaptic plasticity in spiking neural networks
We propose that in order to harness our understanding of neuroscience toward machine
learning, we must first have powerful tools for training brain-like models of learning …
learning, we must first have powerful tools for training brain-like models of learning …
Synaptic motor adaptation: A three-factor learning rule for adaptive robotic control in spiking neural networks
Legged robots operating in real-world environments must possess the ability to rapidly
adapt to unexpected conditions, such as changing terrains and varying payloads. This paper …
adapt to unexpected conditions, such as changing terrains and varying payloads. This paper …
Learning to learn online with neuromodulated synaptic plasticity in spiking neural networks
S Schmidgall, J Hays - ar** the connectomes of many new
species, including the near completion of the Drosophila melanogaster. It is important to ask …
species, including the near completion of the Drosophila melanogaster. It is important to ask …
Reinforcement Learning for Spiking Neural Networks
KCM Van den Berghe - 2024 - repository.tudelft.nl
Enabling embodied intelligence in robotics presents several unique challenges. A first major
concern is the need for energy efficiency, low latency, and strong temporal reasoning to …
concern is the need for energy efficiency, low latency, and strong temporal reasoning to …