├── Technique └── Capsule Network │ └── README.md └── README.md /Technique/Capsule Network/README.md: -------------------------------------------------------------------------------- 1 | # Capsule Network 2 | 3 | ## Theory 4 | - **Dynamic Routing Between Capsules.** *Sara Sabour, Nicholas Frosst, Geoffrey E. Hinton.* NIPS 2017 [paper](https://arxiv.org/abs/1710.09829) 5 | - **Matrix capsules with EM routing.** *Geoffrey E. Hinton, Sara Sabour, Nicholas Frosst.* ICLR 2018 [paper](https://openreview.net/pdf?id=HJWLfGWRb) 6 | - **Stacked Capsule Autoencoders.** *Adam R. Kosiorek, Sara Sabour, Yee Whye Teh, Geoffrey E. Hinton.* NeurIPS 2019 [paper](https://arxiv.org/abs/1906.06818) 7 | - **STAR-Caps: Capsule Networks with Straight-Through Attentive Routing.** *Karim Ahmed, Lorenzo Torresani.* NeurIPS 2019 [paper]() 8 | - **Group Equivariant Capsule Networks.** *Jan Eric Lenssen, Matthias Fey, Pascal Libuschewski.* NeurIPS 2018 [paper]() 9 | - **Limitations of routing-by-agreement based capsule networks.** *.* 10 | 11 | ## Application 12 | - **Capsule Graph Neural Network.** *Zhang Xinyi, Lihui Chen.* ICLR 2019 [paper](https://openreview.net/pdf?id=Byl8BnRcYm) 13 | - **Graph Capsule Convolutional Neural Networks.** *Saurabh Verma, Zhi-Li Zhang.* [paper](https://arxiv.org/abs/1805.08090) 14 | - **Directional and Explainable Serendipity Recommendation.** *.* WWW 2020？ [paper](https://cis.temple.edu/~jiewu/research/publications/Publication_files/jiang_www_2020.pdf) 15 | - **A Capsule Network for Recommendation and Explaining What You Like and Dislike.** *Chenliang Li, Cong Quan, Li Peng, Yunwei Qi, Yuming Deng, Libing Wu.* SIGIR 2019 [paper](https://arxiv.org/abs/1907.00687) 16 | - **Multi-Interest Network with Dynamic Routing for Recommendation at Tmall.** *Chao Li, Zhiyuan Liu, Mengmeng Wu, Yuchi Xu, Huan Zhao, Pipei Huang, Guoliang Kang, Qiwei Chen, Wei Li, Dik Lun Lee.* CIKM 2019 [paper](https://arxiv.org/abs/1904.08030) 17 | - **Information Aggregation for Multi-Head Attention with Routing-by-Agreement.** *Jian Li, Baosong Yang, Zi-Yi Dou, Xing Wang, Michael R. Lyu, Zhaopeng Tu.* NAACL 2019 [paper]() 18 | - **A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization.** *Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung.* NAACL 2019 [paper](https://arxiv.org/abs/1808.04122) 19 | - **Attention-Based Capsule Networks with Dynamic Routing for Relation Extraction.** *Ningyu Zhang, Shumin Deng, Zhanlin Sun, Xi Chen, Wei Zhang, Huajun Chen.* EMNLP 2018 [paper]https://www.aclweb.org/anthology/D18-1120.pdf) 20 | - **CapDRL: A Deep Capsule Reinforcement Learning for Movie Recommendation.** * Chenfei Zhao, Lan Hu.* PRICAI 2019 [paper]() 21 | - **Few-Shot Text Classification with Induction Network.** *Ruiying Geng, Binhua Li, Yongbin Li, Yuxiao Ye, Ping Jian, Jian Sun.* 2019 [paper]() 22 | - **A capsule network for traffic speed prediction in complex road networks.** *Youngjoo Kim, Peng Wang, Yifei Zhu, Lyudmila Mihaylova.* 2018 [paper]() 23 | 24 | ## Other 25 | * [Awesome Capsule Networks](https://github.com/sekwiatkowski/awesome-capsule-networks) - capsule network 资源汇总 26 | 27 | 28 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # DeepLearningResource 2 | *Deep learning resource. Your contributions are always welcome!* 3 | 4 | ## [Conference Deadlines](https://sites.google.com/site/lyangwww/resources) 5 | 6 | ## Classic Technique 7 | * Machine Learning 8 | * [Foundations of Machine Learning](https://cs.nyu.edu/~mohri/mlbook/) - Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar (强烈推荐) 9 | * 机器学西（西瓜书） - 周志华 10 | 11 | * Deep Learning 12 | * [Hung-yi Lee 深度学习](https://www.bilibili.com/video/av48285039) - 李宏毅深度学习（完整版）课程（2019） 13 | * [CMU课程：《深度学习进阶(2020)》](https://andrejristeski.github.io/10707-S20/) 14 | * [纽约大学2020年Yann LeCun讲授的深度学习课程](https://drive.google.com/drive/folders/1-9th2FpFJy5OnfoVU_9_Dc1SgSjgnw8w) - “Deep Learning – SP20 | New York University” by Yann LeCun 15 | * [贝叶斯深度学习](https://sites.cs.ucsb.edu/~william/papers/BDL.pdf) - 简洁易懂的《贝叶斯深度学习》教程 by 肖逸君 16 | * Generative Adversarial Network 17 | * [Hung-yi Lee 对抗生成网络](https://www.bilibili.com/video/av24011528) - 李宏毅对抗生成网络(GAN)课程(2018) 18 | * Reinforcement Learning 19 | * [Hung-yi Lee 强化学习](https://www.bilibili.com/video/av24724071) - 李宏毅深度强化学习课程(2018) 20 | * Graphical Model 21 | * [概率图模型基础](https://www.bilibili.com/video/av33545406) - 概率图模型基础，白板推导系列。 22 | * Expectation Maximization 23 | * [人人都懂EM算法](https://zhuanlan.zhihu.com/p/36331115) - 知乎关于EM算法的介绍文章 24 | 25 | ## Advanced Technique 26 | * Graph Neural Network 27 | * Self-Supervised Learning 28 | * [Yan Lecun：自监督学习] - [视频搬运](https://www.bilibili.com/video/av88129135/) [Slides](https://drive.google.com/file/d/1r-mDL4IX_hzZLDBKp8_e8VZqD7fOzBkF/view) 29 | * Causal Model 30 | * [因果模型概览](https://plato.stanford.edu/entries/causal-models/) -《Causal Models | Stanford Encyclopedia of Philosophy》 31 | * [《统计学因果推理：初级读本》样章(预览)](http://bayes.cs.ucla.edu/PRIMER/) -《Causal Inference in Statistics: A Primer》by Judea Pearl, Madelyn Glymour, Nicholas P. Jewell 32 | * [《因果推理原理：基础与学习算法》](https://mitpress.mit.edu/books/elements-causal-inference) -《Elements of Causal Inference - Foundations and Learning Algorithms | The MIT Press》by Jonas Peters, Dominik Janzing and Bernhard Schölkopf (MIT 2017) [下载](https://www.dropbox.com/s/gkmsow492w3oolt/11283.pdf?dl=1) [pdf](https://pan.baidu.com/s/1RzvyuVnMjSfRHKRKmNd0Yg) 33 | * [Causality for Machine Learning](https://arxiv.org/abs/1911.10500) - 关于因果关系在机器学习的综述，by 德国著名机器学者Bernhard Schölkopf 34 | * [Capsule Network](https://github.com/ShanleiMu/DeepLearningResource/tree/master/Technique/Capsule%20Network) 35 | 36 | ## Recommender System 37 | * [LDA及其在推荐系统中的应用](https://medium.com/m/global-identity?redirectUrl=https%3A%2F%2Fblog.rosetta.ai%2Fa-deep-dive-into-latent-dirichlet-allocation-lda-and-its-applications-on-recommender-system-e2e8ea5e661c) - 《A Deep Dive into Latent Dirichlet Allocation (LDA) and Its Applications on Recommender System》by Kung-Hsiang, Huang 38 | 39 | 40 | ## Coding 41 | * Python 42 | * [Think Python 2e 最新版中文翻译](https://codingpy.com/books/thinkpython2/) 43 | * PyTorch 44 | * [Deep Learning with PyTorch](https://www.manning.com/books/deep-learning-with-pytorch) - 官方权威教程书，可以免费在线看，购买需要付费 45 | * [Deep Learning with PyTorch](https://pytorch.org/assets/deep-learning/Deep-Learning-with-PyTorch.pdf) - 免费的前5章 46 | * [PyTorch Tricks](https://github.com/zxdefying/pytorch_tricks) - PyTorch Tricks 47 | * [PyTorch 有哪些坑/bug？](https://www.zhihu.com/question/67209417) - PyTorch 有哪些坑/bug？ 48 | 49 | ## Foundation of Mathematics 50 | * Foundation of Data Science - 数据科学基础，图灵奖得主John Hopcroft等人撰写的专著。 51 | * Linear Algebra 52 | * [Hung-yi Lee 线性代数](https://www.bilibili.com/video/av31780632) - 李宏毅线性代数课程(2018) 53 | * [MIT 线性代数](https://www.bilibili.com/video/av15463995) - MIT 18.06 Linear Algebra, Spring 2005 中英双语字幕 54 | * [袖珍书:矩阵攻略](http://www2.imm.dtu.dk/pubdb/views/publication_details.php?id=3274) - 《The Matrix Cookbook》KB Petersen, MS Pedersen (2012) 55 | * [哈佛《神经科学数学工具》课程——用神经数据集讲解线性代数、微分方程、概率与统计等数学概念(Matlab)](https://canvas.harvard.edu/courses/71556) - 《NEUROBIO 314QC: Mathematical Tools for Neuroscience》by Lucy Lai, Alex Chen 56 | * Calculus 57 | * Probability Theory 58 | 59 | ## Research Tools 60 | * Gnuplot 61 | * [Gnuplot 中文教程](http://blog.sciencenet.cn/blog-373392-535918.html) 62 | * LaTex 63 | * [ACM LaTex 模板](https://www.acm.org/publications/proceedings-template) 64 | * [LaTeX 入门文档](https://liam.page/2014/09/08/latex-introduction/) 65 | * [常用符号LaTeX表示](http://www.mohu.org/info/symbols/symbols.htm) 66 | * T-SNE 67 | * [介绍](https://www.oreilly.com/learning/an-illustrated-introduction-to-the-t-sne-algorithm) 68 | * Knowledge Graph Tools 69 | * [Google KG Search API](https://developers.google.com/knowledge-graph/) 70 | * Matrix Calculus 71 | * [Matrix Calculus](https://en.wikipedia.org/wiki/Matrix_calculus) 72 | * Graph 73 | * [GraphVite](https://graphvite.io/) - A general and high-performance graph embedding system for various applications 74 | designed for CPU-GPU hybrid architecture 75 | * Vim 76 | * [Vim 总结](https://zhuanlan.zhihu.com/p/76787950)- 学会这21条，你离 Vim 大神就不远了！ 77 | * [Draw.io](https://github.com/jgraph/drawio) - Draw.io在线图表制作网站. 78 | * [DL相关会议录用率](https://github.com/lixin4ever/Conference-Acceptance-Rate) 79 | * [论文模板与自查清单](https://www.aje.com/dist/docs/Developmental_Editing_Report_Template_2015.pdf) - Developmental Editing Report --------------------------------------------------------------------------------