├── README.md ├── frameworks ├── chainer.md ├── gensim.md ├── pyLDAvis.md ├── pyevolve.md └── xgboost.md ├── papernotes ├── 2014 │ ├── 10 │ │ └── explain-images-multimodel-recurrent-neural-networks.md │ └── 06 │ │ └── model-visualizing-summarising-conv-net.md ├── 2015 │ └── 09 │ │ ├── document-modeling-with-GRU.md │ │ └── hierarchical-rnn-for-document-modeling.md └── 2016 │ ├── 02 │ ├── conv-attention-network-source-code-summarization.md │ ├── document-context-language-models.md │ └── planet-photo-geolocation.md │ ├── 03 │ └── Learning-Discriminate-Features-Using-Encoder-Decoder.md │ ├── 05 │ ├── not-just-a-black-box-deep-feature-learning.md │ └── tweet2vec.md │ ├── 06 │ ├── hybrid-recommender-system-based-on-autoencoders.md │ └── vote-boosting-ensembles.md │ └── 07 │ ├── Bag-Of-Tricks-For-Efficient-Text-Classification.md │ ├── Domain-Adaption-for-Neural-Network-by-Parameter-Augmentation.md │ └── LSTM-Encoder-Decoder-For-Multi-Sensor-Anomaly-Detection.md └── research ├── seq2seq.md └── 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