no code implementations • NeurIPS 2014 • Aaron Van Den Oord, Benjamin Schrauwen
In this paper we propose a new scalable deep generative model for images, called the Deep Gaussian Mixture Model, that is a straightforward but powerful generalization of GMMs to multiple layers.
Ranked #69 on Image Generation on CIFAR-10 (bits/dimension metric)
no code implementations • 9 Jun 2014 • Juan Pablo Carbajal, Joni Dambre, Michiel Hermans, Benjamin Schrauwen
In this work, we explore the use of memristor networks for analog approximate computation, based on a machine learning framework called reservoir computing.
no code implementations • NeurIPS 2013 • Michiel Hermans, Benjamin Schrauwen
In this pa- per we study the effect of a hierarchy of recurrent neural networks on processing time series.
no code implementations • NeurIPS 2013 • Aaron Van Den Oord, Sander Dieleman, Benjamin Schrauwen
We also show that recent advances in deep learning translate very well to the music recommendation setting, with deep convolutional neural networks significantly outperforming the traditional approach.
no code implementations • NeurIPS 2012 • Anteo Smerieri, François Duport, Yvon Paquot, Benjamin Schrauwen, Marc Haelterman, Serge Massar
Operating speeds allowing for real time information operation have been reached using optoelectronic systems.
no code implementations • NeurIPS 2012 • Pieter-Jan Kindermans, Hannes Verschore, David Verstraeten, Benjamin Schrauwen
The usability of Brain Computer Interfaces (BCI) based on the P300 speller is severely hindered by the need for long training times and many repetitions of the same stimulus.
no code implementations • NeurIPS 2010 • Fabian Triefenbach, Azarakhsh Jalalvand, Benjamin Schrauwen, Jean-Pierre Martens
Automatic speech recognition has gradually improved over the years, but the reliable recognition of unconstrained speech is still not within reach.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1