NeurIPS 2014

Sequence to Sequence Learning with Neural Networks

NeurIPS 2014 farizrahman4u/seq2seq

Our method uses a multilayered Long Short-Term Memory (LSTM) to map the input sequence to a vector of a fixed dimensionality, and then another deep LSTM to decode the target sequence from the vector.

MACHINE TRANSLATION TRAFFIC PREDICTION

Semi-Supervised Learning with Deep Generative Models

NeurIPS 2014 probtorch/probtorch

The ever-increasing size of modern data sets combined with the difficulty of obtaining label information has made semi-supervised learning one of the problems of significant practical importance in modern data analysis.

BAYESIAN INFERENCE

Recurrent Models of Visual Attention

NeurIPS 2014 kevinzakka/recurrent-visual-attention

Applying convolutional neural networks to large images is computationally expensive because the amount of computation scales linearly with the number of image pixels.

IMAGE CLASSIFICATION

Discovering Structure in High-Dimensional Data Through Correlation Explanation

NeurIPS 2014 gregversteeg/CorEx

We introduce a method to learn a hierarchy of successively more abstract representations of complex data based on optimizing an information-theoretic objective.

On the Computational Efficiency of Training Neural Networks

NeurIPS 2014 scikit-learn-contrib/polylearn

It is well-known that neural networks are computationally hard to train.

Depth Map Prediction from a Single Image using a Multi-Scale Deep Network

NeurIPS 2014 MasazI/cnn_depth_tensorflow

Predicting depth is an essential component in understanding the 3D geometry of a scene.

Two-Stream Convolutional Networks for Action Recognition in Videos

NeurIPS 2014 woodfrog/ActionRecognition

Our architecture is trained and evaluated on the standard video actions benchmarks of UCF-101 and HMDB-51, where it is competitive with the state of the art.

ACTION CLASSIFICATION ACTION RECOGNITION IN VIDEOS MULTI-TASK LEARNING OPTICAL FLOW ESTIMATION

Content-based recommendations with Poisson factorization

NeurIPS 2014 premgopalan/collabtm

We develop collaborative topic Poisson factorization (CTPF), a generative model of articles and reader preferences.

RECOMMENDATION SYSTEMS

Learning to Discover Efficient Mathematical Identities

NeurIPS 2014 kkurach/math_learning

In this paper we explore how machine learning techniques can be applied to the discovery of efficient mathematical identities.

LSDA: Large Scale Detection Through Adaptation

NeurIPS 2014 jhoffman/lsda

A major challenge in scaling object detection is the difficulty of obtaining labeled images for large numbers of categories.

OBJECT CLASSIFICATION OBJECT DETECTION