https://aman.ai/primers/ai/top-30-papers/

• [x] The First Law of Complexodynamics
• [x] The Unreasonable Effectiveness of Recurrent Neural Networks
• [x] Understanding LSTM Networks
• [x] Recurrent Neural Network Regularization
• [x] Keeping Neural Networks Simple by Minimizing the Description Length of the Weights
• [x] Pointer Networks
• [x] ImageNet Classification with Deep Convolutional Neural Networks
• [x] Order Matters: Sequence to Sequence for Sets
• [x] GPipe: Easy Scaling with Micro-Batch Pipeline Parallelism
• [x] Deep Residual Learning for Image Recognition
• [x] Multi-Scale Context Aggregation by Dilated Convolutions
• [x] Neural Message Passing for Quantum Chemistry
• [x] Attention is All You Need
• [x] Neural Machine Translation by Jointly Learning to Align and Translate
• [x] Identity Mappings in Deep Residual Networks
• [x] A Simple Neural Network Module for Relational Reasoning
• [x] Variational Lossy Autoencoder
• [x] Relational Recurrent Neural Networks
• [x] Quantifying the Rise and Fall of Complexity in Closed Systems: the Coffee Automaton