No need stupid moving texts.

CS231n: Convolutional Neural Networks for Visual Recognition - https://cs231n.github.io/

The Unreasonable Effectiveness of Recurrent Neural Networks - https://karpathy.github.io/2015/05/21/rnn-effectiveness/

Understanding LSTM Networks - https://colah.github.io/posts/2015-08-Understanding-LSTMs/

ImageNet Classification with Deep Convolutional Neural Networks - https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436...

Deep Residual Learning for Image Recognition - https://arxiv.org/abs/1512.03385

Multi-Scale Context Aggregation by Dilated Convolutions - https://arxiv.org/abs/1511.07122

Identity Mappings in Deep Residual Networks - https://arxiv.org/abs/1603.05027

Recurrent Neural Network Regularization - https://arxiv.org/abs/1409.2329

Deep Speech 2: End-to-End Speech Recognition in English and Mandarin - https://arxiv.org/abs/1512.02595

Order Matters: Sequence to Sequence for Sets - https://arxiv.org/abs/1511.06391

Neural Machine Translation by Jointly Learning to Align and Translate - https://arxiv.org/abs/1409.0473

Pointer Networks - https://arxiv.org/abs/1506.03134

Attention Is All You Need - https://arxiv.org/abs/1706.03762

The Annotated Transformer - https://nlp.seas.harvard.edu/annotated-transformer/

Neural Turing Machines - https://arxiv.org/abs/1410.5401

A Simple Neural Network Module for Relational Reasoning - https://arxiv.org/abs/1706.01427

Relational Recurrent Neural Networks - https://arxiv.org/abs/1806.01822

Neural Message Passing for Quantum Chemistry - https://arxiv.org/abs/1704.01212

Scaling Laws for Neural Language Models - https://arxiv.org/abs/2001.08361

GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism - https://arxiv.org/abs/1811.06965

Keeping Neural Networks Simple by Minimizing the Description Length of the Weights - https://www.cs.toronto.edu/~hinton/absps/colt93.pdf

A Tutorial Introduction to the Minimum Description Length Principle - https://arxiv.org/abs/math/0406077

The First Law of Complexodynamics - https://scottaaronson.blog/?p=762

Quantifying the Rise and Fall of Complexity in Closed Systems: The Coffee Automaton - https://arxiv.org/abs/1405.6903

Kolmogorov Complexity - https://onlinelibrary.wiley.com/doi/book/10.1002/047174882X

Variational Lossy Autoencoder - https://arxiv.org/abs/1611.02731

Machine Super Intelligence - https://www.vetta.org/documents/Machine_Super_Intelligence.p...

Upvoted. Did you compile that list just now, pulled it from bookmarks, or other source?

this is a goldmine, worth bookmarking.