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Found 4 papers, 3 papers with code
Visualizing and Understanding Convolutional Networks
Large Convolutional Network models have recently demonstrated impressive classification performance on the ImageNet benchmark.
Stochastic Pooling for Regularization of Deep Convolutional Neural Networks
We introduce a simple and effective method for regularizing large convolutional neural networks.
Ranked #39 on
Image Classification
on SVHN
ADADELTA: An Adaptive Learning Rate Method
We present a novel per-dimension learning rate method for gradient descent called ADADELTA.
Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines
We present a type of Temporal Restricted Boltzmann Machine that defines a probability distribution over an output sequence conditional on an input sequence.
