Add to ORKGThis paper introduces enhancements to the Spike-Prop algorithm [1], an error-backpropagation learning rule suited for spiking neurons using exact spike time coding. These enhancements provide additional learning rules for the synaptic delays, time constants and for the neurons' thresholds. This results in less constrained network topologies (the XOR problem for example needs up to 10 times less weights and learning convergence is up to two times faster)
Precise spike timing as a means to encode information in neural networks is biologically supported, ...
Precise spike timing as a means to encode information in neural networks is biologically supported, ...
Precise spike timing as a means to encode information in neural networks is biologically supported, ...
This paper introduces enhancements to the Spike-Prop algorithm [1], an error-backpropagation learnin...
Abstract. For a network of spiking neurons with reasonable post-synaptic potentials, we derive a sup...
A spiking neurons network encodes information in the timing of individual spike times. A novel super...
textabstractFor a network of spiking neurons that encodes information in the timing of individual sp...
For a network of spiking neurons that encodes information in the timing of individual spike-times, w...
A spiking neurons network encodes information in the timing of individual spike times. A novel super...
Abstract—SpikeProp is a supervised learning algorithm for spiking neural networks analogous to backp...
A common learning task for a spiking neuron is to map a spatiotemporal input pattern to a target out...
SummaryTo signal the onset of salient sensory features or execute well-timed motor sequences, neuron...
Spiking Neural Networks (SNNs) are a pathway that could potentially empower low-power event-driven n...
The main contribution of this paper is the derivation of a steepest gradient descent learning rule f...
International audienceThe main contribution of this paper is the derivation of a steepest gradient d...
Precise spike timing as a means to encode information in neural networks is biologically supported, ...
Precise spike timing as a means to encode information in neural networks is biologically supported, ...
Precise spike timing as a means to encode information in neural networks is biologically supported, ...
This paper introduces enhancements to the Spike-Prop algorithm [1], an error-backpropagation learnin...
Abstract. For a network of spiking neurons with reasonable post-synaptic potentials, we derive a sup...
A spiking neurons network encodes information in the timing of individual spike times. A novel super...
textabstractFor a network of spiking neurons that encodes information in the timing of individual sp...
For a network of spiking neurons that encodes information in the timing of individual spike-times, w...
A spiking neurons network encodes information in the timing of individual spike times. A novel super...
Abstract—SpikeProp is a supervised learning algorithm for spiking neural networks analogous to backp...
A common learning task for a spiking neuron is to map a spatiotemporal input pattern to a target out...
SummaryTo signal the onset of salient sensory features or execute well-timed motor sequences, neuron...
Spiking Neural Networks (SNNs) are a pathway that could potentially empower low-power event-driven n...
The main contribution of this paper is the derivation of a steepest gradient descent learning rule f...
International audienceThe main contribution of this paper is the derivation of a steepest gradient d...
Precise spike timing as a means to encode information in neural networks is biologically supported, ...
Precise spike timing as a means to encode information in neural networks is biologically supported, ...
Precise spike timing as a means to encode information in neural networks is biologically supported, ...