Neural Networks
136 papers
Papers per year
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22
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Papers
Efficient and direct estimation of a neural subunit model for sensory coding
NeurIPS 2012
Efficient Spike-Coding with Multiplicative Adaptation in a Spike Response Model
NeurIPS 2012
Learning optimal spike-based representations
NeurIPS 2012
Spiking and saturating dendrites differentially expand single neuron computation capacity
NeurIPS 2012
Waveform Driven Plasticity in BiFeO3 Memristive Devices: Model and Implementation
NeurIPS 2012
Active dendrites: adaptation to spike-based communication
NeurIPS 2011
Expressive Power and Approximation Errors of Restricted Boltzmann Machines
NeurIPS 2011
Policy Gradient Coagent Networks
NeurIPS 2011
Sequence learning with hidden units in spiking neural networks
NeurIPS 2011
Shallow vs. Deep Sum-Product Networks
NeurIPS 2011
Attractor Dynamics with Synaptic Depression
NeurIPS 2010
A VLSI Implementation of the Adaptive Exponential Integrate-and-Fire Neuron Model
NeurIPS 2010
Implicit encoding of prior probabilities in optimal neural populations
NeurIPS 2010
Inferring Stimulus Selectivity from the Spatial Structure of Neural Network Dynamics
NeurIPS 2010
Over-complete representations on recurrent neural networks can support persistent percepts
NeurIPS 2010
Spike timing-dependent plasticity as dynamic filter
NeurIPS 2010
A Neural Implementation of the Kalman Filter
NeurIPS 2009
Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learning
NeurIPS 2009
Kernel Methods for Deep Learning
NeurIPS 2009
Predicting the Optimal Spacing of Study: A Multiscale Context Model of Memory
NeurIPS 2009
Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks
NeurIPS 2009
Artificial Olfactory Brain for Mixture Identification
NeurIPS 2008
Hebbian Learning of Bayes Optimal Decisions
NeurIPS 2008
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing
NeurIPS 2008
On the asymptotic equivalence between differential Hebbian and temporal difference learning using a local third factor
NeurIPS 2008