Search Results

Adversarial Training Methods for Semi-Supervised Text Classification

tensorflow/models 25 May 2016

We extend adversarial and virtual adversarial training to the text domain by applying perturbations to the word embeddings in a recurrent neural network rather than to the original input itself.

General Classification Semi Supervised Text Classification +3

MobileNetV2: Inverted Residuals and Linear Bottlenecks

tensorflow/models CVPR 2018

In this paper we describe a new mobile architecture, MobileNetV2, that improves the state of the art performance of mobile models on multiple tasks and benchmarks as well as across a spectrum of different model sizes.

Image Classification Object Detection +3

AutoAugment: Learning Augmentation Policies from Data

tensorflow/models 24 May 2018

In our implementation, we have designed a search space where a policy consists of many sub-policies, one of which is randomly chosen for each image in each mini-batch.

Fine-Grained Image Classification Image Augmentation

Identity Mappings in Deep Residual Networks

tensorflow/models 16 Mar 2016

Deep residual networks have emerged as a family of extremely deep architectures showing compelling accuracy and nice convergence behaviors.

Image Classification

Cognitive Mapping and Planning for Visual Navigation

tensorflow/models CVPR 2017

The accumulated belief of the world enables the agent to track visited regions of the environment.

Visual Navigation

Ensemble Adversarial Training: Attacks and Defenses

tensorflow/models ICLR 2018

We show that this form of adversarial training converges to a degenerate global minimum, wherein small curvature artifacts near the data points obfuscate a linear approximation of the loss.

Very Deep Convolutional Networks for Large-Scale Image Recognition

tensorflow/models 4 Sep 2014

In this work we investigate the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting.

General Classification Image Classification

Weight Uncertainty in Neural Networks

tensorflow/models 20 May 2015

We introduce a new, efficient, principled and backpropagation-compatible algorithm for learning a probability distribution on the weights of a neural network, called Bayes by Backprop.

Bayesian Inference General Classification

Swivel: Improving Embeddings by Noticing What's Missing

tensorflow/models 6 Feb 2016

We present Submatrix-wise Vector Embedding Learner (Swivel), a method for generating low-dimensional feature embeddings from a feature co-occurrence matrix.

Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling

tensorflow/models ICLR 2018

At the same time, advances in approximate Bayesian methods have made posterior approximation for flexible neural network models practical.

Decision Making Multi-Armed Bandits