Robert Tinn

Artificial Intelligence · 2020–2023

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 55 citations into it
• Natural Language Processing — 25 citations into it
• Representation & Self-Supervised Learning — 12 citations into it

Whom Robert Tinn trusts overall

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

1. Diederik P. Kingma
2. Alec Radford
3. Geoffrey E. Hinton
4. Percy Liang
5. Yoshua Bengio
6. Tomas Mikolov
7. Jimmy Ba
8. Alex Krizhevsky
9. Ilya Sutskever
10. Richard Socher

Who trusts Robert Tinn overall

1. Michihiro Yasunaga

Papers from Robert Tinn's perspective

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

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

Their papers

• Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing (2020) — 2,598 citations
• BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs (2023) — 661 citations