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Found 7 papers, 0 papers with code
Factoring Variations in Natural Images with Deep Gaussian Mixture Models
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)
Memristor models for machine learning
In this work, we explore the use of memristor networks for analog approximate computation, based on a machine learning framework called reservoir computing.
Training and Analysing Deep Recurrent Neural Networks
In this pa- per we study the effect of a hierarchy of recurrent neural networks on processing time series.
Deep content-based music recommendation
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.
Analog readout for optical reservoir computers
Operating speeds allowing for real time information operation have been reached using optoelectronic systems.
A P300 BCI for the Masses: Prior Information Enables Instant Unsupervised Spelling
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.
Phoneme Recognition with Large Hierarchical Reservoirs
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
