Josh Payne

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it
• Natural Language Processing — 10 citations into it
• Computational Theory and Mathematics — 9 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it
• Graph Learning — 7 citations into it
• Molecular Biology — 6 citations into it
• Model Architectures — 5 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Josh Payne trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Sepp Hochreiter
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Dzmitry Bahdanau
5. Tomas Mikolov
6. J. Urgen Schmidhuber
7. Diederik P. Kingma
8. Thomas Kipf
9. Jacob Devlin
10. Max Welling

Papers from Josh Payne's perspective

Ordered by how strongly the researchers Josh Payne trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Long Short-Term Memory
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• BERT Learns (and Teaches) Chemistry (2020) — 10 citations