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Found 7 papers, 1 papers with code
Empirical Comparison between Cross-Validation and Mutation-Validation in Model Selection
Mutation validation (MV) is a recently proposed approach for model selection, garnering significant interest due to its unique characteristics and potential benefits compared to the widely used cross-validation (CV) method.
Runtime Construction of Large-Scale Spiking Neuronal Network Models on GPU Devices
Simulation speed matters for neuroscientific research: this includes not only how quickly the simulated model time of a large-scale spiking neuronal network progresses, but also how long it takes to instantiate the network model in computer memory.
Emergent communication enhances foraging behaviour in evolved swarms controlled by Spiking Neural Networks
In computational models, self-coordination in swarms has been implemented using probabilistic or simple action rules to shape the decision of each agent and the collective behavior.
Phenomenological modeling of diverse and heterogeneous synaptic dynamics at natural density
This chapter sheds light on the synaptic organization of the brain from the perspective of computational neuroscience.
Exploring hyper-parameter spaces of neuroscience models on high performance computers with Learning to Learn
Neuroscience models commonly have a high number of degrees of freedom and only specific regions within the parameter space are able to produce dynamics of interest.
Closed loop interactions between spiking neural network and robotic simulators based on MUSIC and ROS
In order to properly assess the function and computational properties of simulated neural systems, it is necessary to account for the nature of the stimuli that drive the system.
Reconstruction of recurrent synaptic connectivity of thousands of neurons from simulated spiking activity
Here we present a method for the reconstruction of large recurrent neuronal networks from thousands of parallel spike train recordings.
