Anna Bair

Artificial Intelligence · 2023

A researcher in the Science corpus: 1 paper; trusts 68 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 56 citations into it
• Efficiency & Compression — 38 citations into it
• Computer Vision and Pattern Recognition — 32 citations into it
• Large Language Models — 19 citations into it
• Electrical and Electronic Engineering — 8 citations into it
• Evaluation & Benchmarks — 8 citations into it

Whom Anna Bair trusts overall

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

1. Geoffrey E. Hinton
2. Yann LeCun
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Yoshua Bengio
6. Kaiming He
7. Ilya Sutskever
8. Jonathan Frankle
9. Song Han
10. Jia Deng

Papers from Anna Bair's perspective

Ordered by how strongly the researchers Anna Bair 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. ImageNet: A large-scale hierarchical image database
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• A Simple and Effective Pruning Approach for Large Language Models (2023) — 914 citations