47 citations · 147 across the 15 of their papers we have counts for
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EEGSN: Towards Efficient Low-latency Decoding of EEG with Graph Spiking Neural Networks
Xi Chen, Siwei Mai, Konstantinos Michmizos
A vast majority of spiking neural networks (SNNs) are trained based on inductive biases that are not necessarily a good fit for several critical tasks that require low-latency and…
BioGrad: Biologically Plausible Gradient-Based Learning for Spiking Neural Networks
Guangzhi Tang, Neelesh Kumar, Ioannis Polykretis +1
Spiking neural networks (SNN) are delivering energy-efficient, massively parallel, and low-latency solutions to AI problems, facilitated by the emerging neuromorphic chips. To harn…
Increasing Liquid State Machine Performance with Edge-of-Chaos Dynamics Organized by Astrocyte-modulated Plasticity
Vladimir A. Ivanov, Konstantinos P. Michmizos
The liquid state machine (LSM) combines low training complexity and biological plausibility, which has made it an attractive machine learning framework for edge and neuromorphic co…
Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control
Guangzhi Tang, Neelesh Kumar, Raymond Yoo +1
The energy-efficient control of mobile robots is crucial as the complexity of their real-world applications increasingly involves high-dimensional observation and action spaces, wh…
An Astrocyte-Modulated Neuromorphic Central Pattern Generator for Hexapod Robot Locomotion on Intel's Loihi
Ioannis Polykretis, Konstantinos P. Michmizos
Locomotion is a crucial challenge for legged robots that is addressed "effortlessly" by biological networks abundant in nature, named central pattern generators (CPG). The multitud…
Reinforcement co-Learning of Deep and Spiking Neural Networks for Energy-Efficient Mapless Navigation with Neuromorphic Hardware
Guangzhi Tang, Neelesh Kumar, Konstantinos P. Michmizos
Energy-efficient mapless navigation is crucial for mobile robots as they explore unknown environments with limited on-board resources. Although the recent deep reinforcement learni…
Introducing Astrocytes on a Neuromorphic Processor: Synchronization, Local Plasticity and Edge of Chaos
Guangzhi Tang, Ioannis E. Polykretis, Vladimir A. Ivanov +2
While there is still a lot to learn about astrocytes and their neuromodulatory role in the spatial and temporal integration of neuronal activity, their introduction to neuromorphic…