yoongi0428

1. GNN Papers

1) Survey

• Graph Neural Networks: A Review of Methods and Applications, arxiv 2018.
• A Comprehensive Survey on Graph Neural Networks, arxiv 2019.
• A Gentle Introduction to Deep Learning for Graphs.

2) Algorithms

• Semi-Supervised Classification with Graph Convolutional Networks, ICLR 2017. (GCN)
• Inductive representation learning on large graphs (GraphSAGE), NIPS 2017

yoongi0428

0. PyTorch Tutorial
  ☆ - https://github.com/yunjey/pytorch-tutorial
  - https://github.com/yoongi0428/dmlab_torch_tutorial
  
1. Word Embedding
  1) 관련 논문
    - Word2Vec: https://www.aclweb.org/anthology/N13-1090.pdf
    ☆ - Skip-gram: https://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf
  2) 블로그
    ☆ - Jay Alammar "The Illustrated Word2Vec": http://jalammar.github.io/illustrated-word2vec/

yoongi0428

UC 버클리 -  Introduction to Deep Learning (STAT 157)
https://courses.d2l.ai/berkeley-stat-157/syllabus.html
- 강의 + 슬라이드
- 전범위 (Linear regression ~ 최근 NLP, Vision 모델)
- 사용 실습 패키지: MxNet (한글 가이드 https://ko.d2l.ai/)
- 진행중인 강의로 Assignment는 순차 업로드

UCL + DeepMind - Deep Learning Lecture Series
https://www.eventbrite.co.uk/o/ucl-x-deepmind-deep-learning-lecture-series-general-29078980901?fbclid=IwAR1kpPES8IzR2L4oORESUypeZHfvQFiHXsdjZedgltPXpFamjEVNGZVuDxo
- 강의 + 슬라이드 (총 12강)

yoongi0428

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yoongi0428

var bj_main;

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yoongi0428

/*
 *  BytesJack <https://github.com/EtienneLem/bytesjack>
 *
 *  Dev      Etienne Lemay <http://twitter.com/#!/EtienneLem>
 *  Design   Tristan L'abbé <http://twitter.com/#!/_Tristan>
 *
 *  Special thanks to rafBM <http://twitter.com/#!/rafbm> for some JS tricks!
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