This repository contains the resources(papers, blogs, websites, etc.) Ilya recommended to learn about Artificial Intelligence.
- The Annotated Transformer — blog
- The First Law of Complexodynamics — blog
- The Unreasonable Effectiveness of Recurrent Neural Networks — (Andrej Karpathy blog)
- Understanding LSTM Networks – colah’s blog — blog
- Recurrent Neural Network Regularization — arxiv.org
- Keeping NN Simple by Minimizing the Description Legnth of the Weights — PDF
- Pointer Networks — arxiv.org
- ImageNet Classification with Deep Convolutional Neural Networks — PDF
- Order Matters: Sequence to sequence for sets — arxiv.org
- GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism — arxiv.org
- Deep Residual Learning for Image Recognition — arxiv.org
- Multi-Scale Context Aggregation by Dilated Convolutions — arxiv.org
- Neural Message Passing for Quantum Chemistry — arxiv.org
- Attention Is All You Need — arxiv.org
- Neural Machine Translation by Jointly Learning to Align and Translate — arxiv.org
- Identity Mappings in Deep Residual Networks — arxiv.org
- A simple neural network module for relational reasoning — arxiv.org
- Variational Lossy Autoencoder — arxiv.org
- Relational recurrent neural networks — arxiv.org
- Quantifying the Rise and Fall of Complexity in Closed Systems: The Coffee Automaton — arxiv.org
- Neural Turing Machines — arxiv.org
- Deep Speech 2: End-to-End Speech Recognition in English and Mandarin — arxiv.org
- Scaling Laws for Neural Language Models — arxiv.org
- A tutorial introduction to the minimum description length principle — arxiv.org
- Machine Super Intelligence by Shane Legg | BookVersion.dvi — book
- Kolmogorov Complexity and Algorithmic Randomness | lirmm.fr — book
- CS231n Convolutional Neural Networks for Visual Recognition — course