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Found 6 papers, 3 papers with code
Spyx: A Library for Just-In-Time Compiled Optimization of Spiking Neural Networks
As the role of artificial intelligence becomes increasingly pivotal in modern society, the efficient training and deployment of deep neural networks have emerged as critical areas of focus.
NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems
The NeuroBench framework introduces a common set of tools and systematic methodology for inclusive benchmark measurement, delivering an objective reference framework for quantifying neuromorphic approaches in both hardware-independent (algorithm track) and hardware-dependent (system track) settings.
Learning efficient backprojections across cortical hierarchies in real time
Models of sensory processing and learning in the cortex need to efficiently assign credit to synapses in all areas.
Loss shaping enhances exact gradient learning with EventProp in Spiking Neural Networks
Depending on the details of the task and loss function, descending the exact gradient with EventProp can lead to the deletion of important spikes and so to an inadvertent increase of the loss and decrease of classification accuracy and hence a failure to learn.
Scalability and Optimization Strategies for GPU Enhanced Neural Networks (GeNN)
Simulation of spiking neural networks has been traditionally done on high-performance supercomputers or large-scale clusters.
Artificial Olfactory Brain for Mixture Identification
The odor transduction process has a large time constant and is susceptible to various types of noise.
