Aspen K. Hopkins

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it; #30,108 of 35,345 by trust here, #22,463 by citations
• Natural Language Processing — 15 citations into it
• Large Language Models — 9 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it
• Safety, Robustness & Interpretability — 6 citations into it

Whom Aspen K. Hopkins trusts overall

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

1. Alec Radford
2. Yonatan Belinkov
3. Yoshua Bengio
4. Guillaume Alain
5. Geoffrey E. Hinton
6. Ilya Sutskever
7. Diederik P. Kingma
8. Ian Tenney

Who trusts Aspen K. Hopkins overall

1. Michael R Douglas
2. Neel Nanda
3. Samuel Marks
4. Wes Gurnee

Papers from Aspen K. Hopkins's perspective

Ordered by how strongly the researchers Aspen K. Hopkins 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Language Models are Unsupervised Multitask Learners
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. ImageNet: A large-scale hierarchical image database
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task (2022) — 503 citations