- [DeepFaceVariant] Deep Learning Face Representation from Predicting 10,000 Classes. [pdf] [code] ⭐
- Dropout: A Simple Way to Prevent Neural Networks from Overfitting. [pdf]
- Generative Moment Matching Networks. [arxiv] [code]
- [GoogLeNet] Going Deeper with Convolutions. [[pdf](docs/2014/Going Deeper with Convolutions.pdf)] [url] ⭐
- Learning Longer Memory in Recurrent Neural Networks. [url]
- Learning to Execute. [url]
- Network In Network. [[pdf](docs/2014/Network In Network.pdf)] [arxiv] ⭐
- [OverFeat] OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks. [arxiv] [code] ⭐
- Recurrent Neural Network Regularization. [[pdf]](docs/2014/Recurrent Neural Network Regularization.pdf) [url]
- Show and Tell: A Neural Image Caption Generator.[url] ⭐
- [SPPNet] Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition. [arxiv] [keras] ⭐
- Striving for Simplicity: The All Convolutional Net. [arxiv] ⭐
- Towards end-to-end speech recognition with recurrent neural networks.[pdf] ⭐
- [VGGNet] Very Deep Convolutional Networks for Large-Scale Image Recognition. [url] [code] ⭐
- What Regularized Auto-Encoders Learn from the Data. [[pdf]](docs/2014/What Regularized Auto-Encoders Learn from the Data.pdf) [url]
- [GAN] Generative Adversarial Nets. [[pdf]](docs/2014/Generative Adversarial Nets.pdf) [arxiv] [code] ⭐
- [CGNA] Conditional Generative Adversarial Nets. [arxiv] [code] ⭐
- Deep Visual-Semantic Alignments for Generating Image Descriptions. [arxiv] ⭐
- Explaining and Harnessing Adversarial Examples. [arxiv]
- On distinguishability criteria for estimating generative models. [arxiv]
- [VAE] Semi-Supervised Learning with Deep Generative Models. [arxiv] [code] ⭐
- End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results. [arxiv]
- Memory Networks. [arxiv] ⭐
- Multiple Object Recognition with Visual Attention. [url]
- [Attention In NLP First] Neural Machine Translation by Jointly Learning to Align and Translate. [arxiv] [code] ⭐
- [First Memory Paper] Neural Turing Machines. [[pdf]](docs/2014/Neural Turing Machines.pdf) [arxiv] ⭐
- [RAM] Recurrent Models of Visual Attention. [[pdf]](docs/2014/Recurrent Models of Visual Attention.pdf) [arxiv] [tensorflow] ⭐
- [Seq2Seq] Sequence to Sequence Learning with Neural Networks. [[pdf]](docs/2014/Sequence to Sequence Learning with Neural Networks.pdf) [arxiv] [code] ⭐
- Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning, X. Guo et al., NIPS.[url]
- Adaptation regularization: a general framework for transfer learning. [pdf] ⭐
- Heterogeneous Domain Adaptation for Multiple Classes. [pdf]
- Hybrid heterogeneous transfer learning through deep learning. [pdf]
- Learning with Augmented Features for Supervised and Semi-supervised Heterogeneous Domain Adaptation. [pdf]
- Machine learning for targeted display advertising: transfer learning in action. [url]
- Source Free Transfer Learning for Text Classification. [pdf]
- A Convolutional Neural Network for Modelling Sentences. [url]
- Automatic Construction and Natural-Language Description of Nonparametric Regression Models[[pdf]](docs/2014/Automatic Construction and Natural-Language Description of Nonparametric Regression Models(2014).pdf) [url]
- Convolutional Neural Networks for Sentence Classification. [[pdf]](docs/2014/Convolutional Neural Networks for Sentence Classification.pdf) [url]
- Distributed Representations of Sentences and Documents Generating Distribution. [[pdf]](docs/2014/Distributed Representations of Sentences and Documents Generating Distribution.pdf) [url] ⭐
- Effective Use of Word Order for Text Categorization with Convolutional Neural Networks. [url]
- Grammar as a Foreign Language. [url]
- [GRU] Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. [arxiv] ⭐
- On the Properties of Neural Machine Translation- Encoder-Decoder Approaches. [url]
- On Using Very Large Target Vocabulary for Neural Machine Translation. [[pdf]](docs/2014/On Using Very Large Target Vocabulary for Neural Machine Translation.pdf) [url]
- Reading Text in the Wild with Convolutional Neural Networks. [[pdf]](docs/2015/Reading Text in the Wild with Convolutional Neural Networks.pdf) [url]
- [Seq2Seq] Sequence to Sequence Learning with Neural Networks. [[pdf]](docs/2014/Sequence to Sequence Learning with Neural Networks.pdf) [arxiv] [code] ⭐