Ilya 30u30

Ilya 30u30 A Folder from Cosmic The Annotated Transformer The First Law of Complexodynamics The Unreasonable Effectiveness of RNNs Understanding LSTM Networks Recurrent Neural Network Regularization Keeping Neural Networks Simple by Minimizing the Description Length of the Weights Pointer Networks ImageNet Classification with Deep CNNs Order Matters: Sequence to sequence for sets GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism Deep Residual Learning for Image Recognition Multi-Scale Context Aggregation by Dilated Convolutions Neural Quantum Chemistry Attention Is All You Need Neural Machine Translation by Jointly Learning to Align and Translate Identity Mappings in Deep Residual Networks A Simple NN Module for Relational Reasoning Variational Lossy Autoencoder Relational RNNs Quantifying the Rise and Fall of Complexity in Closed Systems: The Coffee Automaton Neural Turing Machines Deep Speech 2: End-to-End Speech Recognition in English and Mandarin Scaling

Ilya 30u30 A Folder from Cosmic The Annotated Transformer ↗ The First Law of Complexodynamics ↗ The Unreasonable Effectiveness of RNNs ↗ Understanding LSTM Networks ↗ Recurrent Neural Network Regularization ↗ Keeping Neural Networks Simple by Minimizing the Description Length of the Weights ↗ Pointer Networks ↗ ImageNet Classification with Deep CNNs ↗ Order Matters: Sequence to sequence for sets ↗ GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism ↗ Deep Residual Learning for Image Recognition ↗ Multi-Scale Context Aggregation by Dilated…

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• Justin Wang
• Elizabeth Qiu
• Kevin Wang
• Asma Lamgh
• Blake Dee
• Atem Aguer
• Sidney Nimako
• Lydia Nottingham
• Jaden Kwan
• Sebastian J Zhao
• Vivek Shukla
• Malaika Aiyar

related reading

• Aman's AI Journal • Primers • Ilya Sutskever's Top 30aman.ai
• The Unreasonable Effectiveness of Recurrent Neural Networkskarpathy.github.io
• The Decade of Deep Learning | Leo Gaobmk.sh
• 30 papers · The reading list Ilya Sutskever gave John Carmack30papers.com
• Understanding Deep Learningudlbook.github.io
• [1807.03819] Universal Transformersarxiv.org
• The Little Book of Deep Learningfleuret.org
• [1409.3215] Sequence to Sequence Learning with Neural Networksarxiv.org
• aman.ai • the art of artificial intelligenceaman.ai
• ImageNet Classification with Deep Convolutional Neural Networksproceedings.neurips.cc
• The Unreasonable Effectiveness of Recurrent Neural Networkskarpathy.github.io
• David Duvenaudcs.toronto.edu