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https://github.com/dsksd/pytorch_models

PyTorch study
https://github.com/dsksd/pytorch_models

deep-learning generative-adversarial-network nlp pytorch vae

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PyTorch study

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# Pytorch Study

파이토치 스터디

관심있는 모든 것(NLP, Generative Model, RL,...)을 더욱 잘 이해하기 위해 코드로 구현해보기
클래식한 모델부터 논문, 튜토리얼, 강의, 블로그를 읽고 이해한 것을 바탕으로
구현해보기 +_+

언젠가 직접 모델링하는 그 날까지...

## 파이썬 3.5 Pytorch 환경 구축해둔 도커

ubuntu 16.04 python 3.5.2 with various of ML/DL packages including tensorflow, sklearn, pytorch

`docker pull dsksd/deepstudy:0.2`

## 1. Deep NLP Models

1. BoWClassifier
2. NGRAM & CBOW
3. LSTM POS Tagger
4. Bidirectional LSTM POS Tagger
5. LSTM batch learning
6. Vanilla Sequence2Sequence (Encoder-Decoder)
7. Sequence2Sequence with Attention
8. Relational Network for bAbI task(in progress)
9. Transformer(Attention is all you need)

### 읽고 구현해보고 싶은 논문 리스트

1. Poincaré Embeddings for Learning Hierarchical Representations
2. Neural Embeddings of Graphs in Hyperbolic Space
3. A Deep Reinforced Model for Abstractive Summarization
4. Controllable Text Generation
5. A simple neural network module for relational reasoning

## 2. Generative Models

1. Basic Auto-Encoder
2. Regularized Auto-Encoder
3. Variational Auto-Encoder
3-1. Appendix1: Entropy and KL-divergence
4. Variational Reccurent Auto-Encoder

## 3. Reinforcement Learning

## 4. Evolutionary Algorithms