Full Resolution Image Compression with Recurrent Neural Networks

CVPR 2017 3 code implementations

As far as we know, this is the first neural network architecture that is able to outperform JPEG at image compression across most bitrates on the rate-distortion curve on the Kodak dataset images, with and without the aid of entropy coding.

IMAGE COMPRESSION

Generating Sequences With Recurrent Neural Networks

4 Aug 201337 code implementations

This paper shows how Long Short-term Memory recurrent neural networks can be used to generate complex sequences with long-range structure, simply by predicting one data point at a time.

TEXT GENERATION

Session-based Recommendations with Recurrent Neural Networks

21 Nov 20157 code implementations

We apply recurrent neural networks (RNN) on a new domain, namely recommender systems.

SESSION-BASED RECOMMENDATIONS

Quaternion Recurrent Neural Networks

ICLR 2019 4 code implementations

Recurrent neural networks (RNNs) are powerful architectures to model sequential data, due to their capability to learn short and long-term dependencies between the basic elements of a sequence.

SPEECH RECOGNITION

Quasi-Recurrent Neural Networks

5 Nov 20164 code implementations

Recurrent neural networks are a powerful tool for modeling sequential data, but the dependence of each timestep's computation on the previous timestep's output limits parallelism and makes RNNs unwieldy for very long sequences.

LANGUAGE MODELLING MACHINE TRANSLATION SENTIMENT ANALYSIS

Conditional Random Fields as Recurrent Neural Networks

ICCV 2015 8 code implementations

Pixel-level labelling tasks, such as semantic segmentation, play a central role in image understanding.

REAL-TIME SEMANTIC SEGMENTATION

De-identification of Patient Notes with Recurrent Neural Networks

10 Jun 20161 code implementation

We compare the performance of the system with state-of-the-art systems on two datasets: the i2b2 2014 de-identification challenge dataset, which is the largest publicly available de-identification dataset, and the MIMIC de-identification dataset, which we assembled and is twice as large as the i2b2 2014 dataset.

FEATURE ENGINEERING

Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex

13 Apr 20161 code implementation

We discuss relations between Residual Networks (ResNet), Recurrent Neural Networks (RNNs) and the primate visual cortex.

Recurrent Neural Network Regularization

8 Sep 201416 code implementations

We present a simple regularization technique for Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) units.

IMAGE CAPTIONING LANGUAGE MODELLING MACHINE TRANSLATION SPEECH RECOGNITION

Bidirectional Quaternion Long-Short Term Memory Recurrent Neural Networks for Speech Recognition

6 Nov 20181 code implementation

Recurrent neural networks (RNN) are at the core of modern automatic speech recognition (ASR) systems.

SPEECH RECOGNITION