- Neural Variational Inference for Text Processing [arXiv]
- Recurrent Dropout without Memory Loss [arXiv]
- One-Shot Generalization in Deep Generative Models [arXiv]
- Recursive Recurrent Nets with Attention Modeling for OCR in the Wild [[arXiv](Recursive Recurrent Nets with Attention Modeling for OCR in the Wild)]
- A New Method to Visualize Deep Neural Networks [[arXiv](A New Method to Visualize Deep Neural Networks)]
- Neural Architectures for Named Entity Recognition [arXiv]
- End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF [arXiv]
- Character-based Neural Machine Translation [arXiv]
- Learning Word Segmentation Representations to Improve Named Entity Recognition for Chinese Social Media [arXiv]
- Architectural Complexity Measures of Recurrent Neural Networks [arXiv]
- Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks [arXiv]
- Recurrent Neural Network Grammars [arXiv]
- Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations [arXiv]
- Contextual LSTM (CLSTM) models for Large scale NLP tasks [arXiv]
- Sequence-to-Sequence RNNs for Text Summarization [arXiv]
- Extraction of Salient Sentences from Labelled Documents [arXiv]
- Learning Distributed Representations of Sentences from Unlabelled Data [arXiv]
- Benefits of depth in neural networks [arXiv]
- Associative Long Short-Term Memory [arXiv]
- Generating images with recurrent adversarial networks [arXiv]
- Exploring the Limits of Language Modeling [arXiv]
- Swivel: Improving Embeddings by Noticing What’s Missing [arXiv]
- WebNav: A New Large-Scale Task for Natural Language based Sequential Decision Making [arXiv]
- Efficient Character-level Document Classification by Combining Convolution and Recurrent Layers [arXiv]
- BinaryNet: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1 [arXiv]
- Learning Discriminative Features via Label Consistent Neural Network [arXiv]
- Pixel Recurrent Neural Networks [arXiv]
- Bitwise Neural Networks [arXiv]
- Long Short-Term Memory-Networks for Machine Reading [arXiv]
- Coverage-based Neural Machine Translation [arXiv]
- Understanding Deep Convolutional Networks [arXiv]
- Training Recurrent Neural Networks by Diffusion [arXiv]
- Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures [arXiv]
- Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism [arXiv]
- Recurrent Memory Network for Language Modeling [arXiv]
- Language to Logical Form with Neural Attention [arXiv]
- Learning to Compose Neural Networks for Question Answering [arXiv]
- The Inevitability of Probability: Probabilistic Inference in Generic Neural Networks Trained with Non-Probabilistic Feedback [arXiv]
- COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images [arXiv]
- Survey on the attention based RNN model and its applications in computer vision [arXiv]
NLP
- Strategies for Training Large Vocabulary Neural Language Models [arXiv]
- Multilingual Language Processing From Bytes [arXiv]
- Learning Document Embeddings by Predicting N-grams for Sentiment Classification of Long Movie Reviews [arXiv]
- Target-Dependent Sentiment Classification with Long Short Term Memory [arXiv]
- Reading Text in the Wild with Convolutional Neural Networks [arXiv]
Vision
- Deep Residual Learning for Image Recognition [arXiv]
- Rethinking the Inception Architecture for Computer Vision [arXiv]
- Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks [arXiv]
- Deep Speech 2: End-to-End Speech Recognition in English and Mandarin [arXiv]
NLP
- Teaching Machines to Read and Comprehend [arxiv]
- Semi-supervised Sequence Learning [arXiv]
- Multi-task Sequence to Sequence Learning [arXiv]
- Alternative structures for character-level RNNs [arXiv]
- Larger-Context Language Modeling [arXiv]
- A Unified Tagging Solution: Bidirectional LSTM Recurrent Neural Network with Word Embedding [arXiv]
- Towards Universal Paraphrastic Sentence Embeddings [arXiv]
- BlackOut: Speeding up Recurrent Neural Network Language Models With Very Large Vocabularies [arXiv]
- Sequence Level Training with Recurrent Neural Networks [arXiv]
- Natural Language Understanding with Distributed Representation [arXiv]
- sense2vec - A Fast and Accurate Method for Word Sense Disambiguation In Neural Word Embeddings [arXiv]
- LSTM-based Deep Learning Models for non-factoid answer selection [arXiv]
Programs
- Neural Random-Access Machines [arxiv]
- Neural Programmer: Inducing Latent Programs with Gradient Descent [arXiv]
- Neural Programmer-Interpreters [arXiv]
- Learning Simple Algorithms from Examples [arXiv]
- Neural GPUs Learn Algorithms [arXiv]
- On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models [arXiv]
Vision
- ReSeg: A Recurrent Neural Network for Object Segmentation [arXiv]
- Deconstructing the Ladder Network Architecture [arXiv]
- Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks [arXiv]
General
- Towards Principled Unsupervised Learning [arXiv]
- Dynamic Capacity Networks [arXiv]
- Generating Sentences from a Continuous Space [arXiv]
- Net2Net: Accelerating Learning via Knowledge Transfer [arXiv]
- A Roadmap towards Machine Intelligence [arXiv]
- Session-based Recommendations with Recurrent Neural Networks [arXiv]
- Regularizing RNNs by Stabilizing Activations [arXiv]
- A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification [arXiv]
- Attention with Intention for a Neural Network Conversation Model [arXiv]
- Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Recurrent Neural Network [arXiv]
- A Survey: Time Travel in Deep Learning Space: An Introduction to Deep Learning Models and How Deep Learning Models Evolved from the Initial Ideas [arXiv]
- A Primer on Neural Network Models for Natural Language Processing [arXiv]
- Character-level Convolutional Networks for Text Classification [arXiv]
- A Neural Attention Model for Abstractive Sentence Summarization [arXiv]
- Poker-CNN: A Pattern Learning Strategy for Making Draws and Bets in Poker Games [arXiv]
- Listen, Attend and Spell [arxiv]
- Character-Aware Neural Language Models [arXiv]
- Improved Transition-Based Parsing by Modeling Characters instead of Words with LSTMs [arXiv]
- Finding Function in Form: Compositional Character Models for Open Vocabulary Word Representation [arXiv]
- Semi-Supervised Learning with Ladder Networks [arXiv]
- Document Embedding with Paragraph Vectors [arXiv]
- Training Very Deep Networks [arXiv]
- A Neural Network Approach to Context-Sensitive Generation of Conversational Responses [arXiv]
- Document Embedding with Paragraph Vectors [arXiv]
- A Neural Conversational Model [arXiv]
- Skip-Thought Vectors [arXiv]
- Pointer Networks [arXiv]
- Spatial Transformer Networks [arXiv]
- Tree-structured composition in neural networks without tree-structured architectures [arXiv]
- Visualizing and Understanding Neural Models in NLP [arXiv]
- Learning to Transduce with Unbounded Memory [arXiv]
- Ask Me Anything: Dynamic Memory Networks for Natural Language Processing [arXiv]
- Deep Knowledge Tracing [arXiv]
- ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks [arXiv]
- Reinforcement Learning Neural Turing Machines [arXiv]
- Correlational Neural Networks [arXiv]
- Distilling the Knowledge in a Neural Network [arXiv]
- End-To-End Memory Networks [arXiv]
- Neural Responding Machine for Short-Text Conversation [arXiv]
- Text Understanding from Scratch [arXiv]
- Show, Attend and Tell: Neural Image Caption Generation with Visual Attention [arXiv]
- Learning Longer Memory in Recurrent Neural Networks [arXiv]
- Neural Turing Machines [arxiv]
- Grammar as a Foreign Langauage [arXiv]
- On Using Very Large Target Vocabulary for Neural Machine Translation [arXiv]
- Effective Use of Word Order for Text Categorization with Convolutional Neural Networks [arXiv]
- Multiple Object Recognition with Visual Attention [arXiv]
- Sequence to Sequence Learning with Neural Networks [arXiv]
- Neural Machine Translation by Jointly Learning to Align and Translate [arxiv]
- On the Properties of Neural Machine Translation: Encoder-Decoder Approaches [arXiv]
- Recurrent Neural Network Regularization [arXiv]
- Very Deep Convolutional Networks for Large-Scale Image Recognition [arXiv]
- Going Deeper with Convolutions [arXiv]
- Convolutional Neural Networks for Sentence Classification [arxiv]
- Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation [arXiv]
- Recurrent Models of Visual Attention [arXiv]
- Generative Adversarial Networks [arXiv]
- A Convolutional Neural Network for Modelling Sentences [arXiv]
- Visualizing and Understanding Convolutional Networks [arXiv]
- DeViSE: A Deep Visual-Semantic Embedding Model [pub]
- Maxout Networks [arXiv]
- Exploiting Similarities among Languages for Machine Translation [arXiv]
- Efficient Estimation of Word Representations in Vector Space [arXiv]
- Natural Language Processing (almost) from Scratch [arXiv]