Martin Rehn

发表

Aspects of memory and representation in cortical computation

Martin Rehn, 2006 .

Sound Ranking Using Auditory Sparse-Code Representations

Samy Bengio, Martin Rehn, Richard F. Lyon, 2009 .

Early sensory representation in cortex optimizes information content in small neural assemblies.

Martin Rehn, Friedrich T. Sommer, 2010 .

Storing and restoring visual input with collaborative rank coding and associative memory

Martin Rehn, Friedrich T. Sommer, F. Sommer, 2006, Neurocomputing.

Attractor dynamics in a modular network model of the cerebral cortex

Martin Rehn, Anders Lansner, Mikael Lundqvist, 2006, Neurocomputing.

Auktoritet och atomsprängning: Hans Pettersson och Cambridge-Wienkontroversen

Martin Rehn, 2001 .

Sound Retrieval and Ranking Using Sparse Auditory Representations

Samy Bengio, Martin Rehn, Richard F. Lyon, 2010, Neural Computation.

A network that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields

Martin Rehn, Friedrich T. Sommer, F. Sommer, 2007, Journal of Computational Neuroscience.

A hybrid model of the primary visual cortex

Martin Rehn, David Silverstein, Anders Lansner, 2011, BMC Neuroscience.

Massively parallel simulation of brain-scale neuronal network models

Örjan Ekeberg, Martin Rehn, Anders Lansner, 2005 .

Attractor dynamics in a modular network model of neocortex

Martin Rehn, Anders Lansner, Mikael Djurfeldt, 2006, Network.

Attractor neural networks with patchy connectivity

Martin Rehn, Anders Lansner, Christopher Johansson, 2006, ESANN.

Tonically driven and self-sustaining activity in the lamprey hemicord: When can they co-exist?

Martin Rehn, Mikael Huss, Martin Rehn, 2007, Neurocomputing.

Large-scale content-based audio retrieval from text queries

Samy Bengio, Martin Rehn, Richard F. Lyon, 2008, MIR '08.

Sequence memory with dynamical synapses

Martin Rehn, Anders Lansner, 2004, Neurocomputing.

Brain-scale simulation of the neocortex on the IBM Blue Gene/L supercomputer

Örjan Ekeberg, Martin Rehn, Anders Lansner, 2008, IBM J. Res. Dev..

A network model for the rapid formation of binary sparse representations of sensory inputs.

Martin Rehn, Friedrich T. Sommer, F. Sommer, 2010 .

Recognition of handwritten digits using sparse codes generated by local feature extraction methods

Martin Rehn, Anders Lansner, Rebecca Steinert, 2006, ESANN.

Some computational aspects of attractor memory

Martin Rehn, 2005 .