Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/m0nologuer/AI-reading-list
Up to date list of the most interesting papers in AI
https://github.com/m0nologuer/AI-reading-list
Last synced: about 1 month ago
JSON representation
Up to date list of the most interesting papers in AI
- Host: GitHub
- URL: https://github.com/m0nologuer/AI-reading-list
- Owner: m0nologuer
- Created: 2015-11-30T03:30:35.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2015-11-30T11:51:55.000Z (about 9 years ago)
- Last Synced: 2024-08-02T05:14:11.103Z (4 months ago)
- Size: 2.93 KB
- Stars: 137
- Watchers: 14
- Forks: 27
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- fucking-lists - AI-reading-list
- awesomelist - AI-reading-list
- lists - AI-reading-list
- collection - AI-reading-list
README
# AI-reading-list
This is my personal list of current AI papers I'm reading/ have yet to read. Just things I think point in interesting directions, or topics I'm interested in.## General
[Tensorflow](http://download.tensorflow.org/paper/whitepaper2015.pdf) - Google's large scale infrastructure project[Representation learning](http://arxiv.org/abs/1206.5538) - survey paper on representation methods
[Adversarial Networks](http://arxiv.org/abs/1406.2661) - framework for generation
[Neural Turing Machine](http://arxiv.org/abs/1410.5401)
## RNN structures
[LTSM](http://web.eecs.utk.edu/~itamar/courses/ECE-692/Bobby_paper1.pdf) - long term short term memory[Memory Networks](http://arxiv.org/abs/1410.3916/) - on adding memory storage
[End to End Memory networks](http://arxiv.org/abs/1503.08895) - Facebook's memory storage
[Neural Programmer](http://arxiv.org/abs/1511.04834) - on adding basic artithmetic operations
[Spatial Transformer](http://arxiv.org/abs/1509.05329) - DeepMind digit classification
[Deep Speech](http://arxiv.org/abs/1412.5567) - speech implementation
## Word Vectors
[word2vec](http://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf) - on creating vectors to represent language, useful for RNN inputs[sense2vec](http://arxiv.org/abs/1511.06388) - on word sense disambiguation
[Infinite Dimensional Word Embeddings](http://arxiv.org/abs/1511.05392) - new
[Skip Thought Vectors](http://arxiv.org/abs/1506.06726) - word representation method
[Adaptive skip-gram](http://arxiv.org/abs/1502.07257) - similar approach, with adaptive properties
## Natural Language
[Neural autocoder for paragraphs and documents](http://arxiv.org/abs/1506.01057) - LTSM representation[LTSM over tree structures](http://arxiv.org/abs/1503.04881)
[Sequence to Sequence Learning](http://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf) - word vectors for machine translation
[Teaching Machines to Read and Comprehend](http://arxiv.org/abs/1506.03340) - DeepMind paper
## Convolutional neural nets
[DRAW](http://jmlr.org/proceedings/papers/v37/gregor15.pdf)- An RNN for image classfication[ImageNet Classification](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks) - popular paper
[A Neural Algorithm of Artistic Style](http://arxiv.org/pdf/1508.06576v1.pdf) - popular papeer
[Generative Adversarial Networks](http://arxiv.org/abs/1511.06434) - unsupervised learning to generate images
##Tutorials
[LTSM RNN in Python](http://iamtrask.github.io/2015/11/15/anyone-can-code-lstm/)[Tensorflow Tutorials](https://github.com/nlintz/TensorFlow-Tutorials)
[K-Means with Tensorflow](https://codesachin.wordpress.com/2015/11/14/k-means-clustering-with-tensorflow/)
##Datasets
[DeepMind Q&A Corpus](https://github.com/deepmind/rc-data/)