scientific article; zbMATH DE number 7274979
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Publication:5134573
zbMath1446.92048MaRDI QIDQ5134573
Stefan Rotter, Ulrich Egert, Tayfun Gürel
Publication date: 17 November 2020
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Neural networks for/in biological studies, artificial life and related topics (92B20) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55) Computational methods for problems pertaining to biology (92-08)
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Cites Work
- Maximum likelihood identification of neural point process systems
- A learning rule for very simple universal approximators consisting of a single layer of perceptrons
- Optimization and applications of echo state networks with leaky- integrator neurons
- Online reservoir adaptation by intrinsic plasticity for backpropagation-decorrelation and echo state learning
- Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations
- Statistical Models
- An Introduction to the Theory of Point Processes
- Advanced Lectures on Machine Learning
- Polychronization: Computation with Spikes
- Analyzing Functional Connectivity Using a Network Likelihood Model of Ensemble Neural Spiking Activity
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