Paper2017
Attention Is All You Need
Vaswani et al.
The 2017 paper that introduced the Transformer architecture
Attention
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Paper2020
Vision Transformer (ViT)
Dosovitskiy et al.
Applying Transformers directly to image patches for visual recognition
Paper2018
Relational Recurrent Neural Networks
Santoro et al.
RNNs with relational memory that enables reasoning across time
Blog2018
The Annotated Transformer
Sasha Rush
Line-by-line PyTorch implementation of the Transformer architecture
Paper2017
A Simple Neural Network Module for Relational Reasoning
Santoro et al.
Relation Networks for learning to reason about object relationships
Paper2015
Order Matters: Sequence to Sequence for Sets
Vinyals, Bengio & Kudlur
How input and output ordering affects seq2seq learning on set-structured data
Paper2015
Pointer Networks
Vinyals, Fortunato & Jaitly
Neural architecture that outputs pointers to input positions, enabling variable-size outputs
Paper2014
Neural Machine Translation by Jointly Learning to Align and Translate
Bahdanau, Cho & Bengio
The paper that introduced the attention mechanism for sequence-to-sequence models
Paper2014
Neural Turing Machines
Graves, Wayne & Danihelka
Neural networks augmented with external memory and attention-based read/write heads