Concept

Highway network

Related publications (52)

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Emergence of Connectivity Motifs in Networks of Model Neurons with Short- and Long-Term Plastic Synapses

Michele Giugliano, Eleni Vasilaki

Recent experimental data from the rodent cerebral cortex and olfactory bulb indicate that specific connectivity motifs are correlated with short-term dynamics of excitatory synaptic transmission. It was observed that neurons with short-term facilitating sy ...

Public Library of Science2014

A modulated gradient model for scalar transport in large-eddy simulation of the atmospheric boundary layer

Fernando Porté Agel, Hao Lu

As a simple alternative to the standard eddy-diffusivity closure, a nonlinear subgrid-scale (SGS) flux model is introduced and implemented in simulations of a neutral atmospheric boundary layer and a stable atmospheric boundary layer. The new model compute ...

American Institute of Physics2013

Evolving Complete Robots with CPPN-NEAT: The Utility of Recurrent Connections

Joshua Evan Auerbach

This paper extends prior work using Compositional Pattern Producing Networks (CPPNs) as a generative encoding for the purpose of simultaneously evolving robot morphology and control. A method is presented for translating CPPNs into complete robots includin ...

ACM Press2011

Robust Discriminative Keyword Spotting for Emotionally Colored Spontaneous Speech using Bidirectional LSTM Networks

In this paper we propose a new technique for robust keyword spotting that uses bidirectional Long Short-Term Memory (BLSTM) recurrent neural nets to incorporate contextual information in speech decoding. Our approach overcomes the drawbacks of generative H ...

2009

Mixture models for unsupervised and supervised learning

In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of al1 this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...

EPFL2000

Mixture Models for Unsupervised and Supervised Learning

In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of all this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...

IDIAP2000

Mixture Models for Unsupervised and Supervised Learning

École Polytechnique Fédérale de Lausanne, Computer Science Department2000

Synchrony generation in recurrent networks with frequency-dependent synapses

Henry Markram

Throughout the neocortex, groups of neurons have been found to fire synchronously on the time scale of several milliseconds. This near coincident firing of neurons could coordinate the multifaceted information of different features of a stimulus. The mecha ...

2000

Classification using localized mixtures of experts

A mixture of experts consists of a gating network that learns to partition the input space and of experts networks attributed to these different regions. This paper focuses on the choice of the gating network. First, a localized gating network based on a m ...

London: IEE1999

Bounds on the Degree of High Order Binary Perceptrons

High order perceptrons are often used in order to reduce the size of neural networks. The complexity of the architecture of a usual multilayer network is then turned into the complexity of the functions performed by each high order unit and in particular b ...

D facto1996