Anne Wu

Artificial Intelligence · with Pino · 2020–2021

A researcher in the Science corpus: 6 papers; trusts 143 researchers and is trusted by 24 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 169 citations into it; #8,487 of 35,345 by trust here, #8,706 by citations
• Speech & Audio — 91 citations into it; #456 of 1,076 by trust here, #420 by citations
• Natural Language Processing — 86 citations into it; #4,456 of 5,688 by trust here, #4,032 by citations
• Machine Translation — 52 citations into it; #72 of 292 by trust here, #87 by citations
• Signal Processing — 45 citations into it
• Computer Vision and Pattern Recognition — 39 citations into it
• Representation & Self-Supervised Learning — 24 citations into it
• Evaluation & Benchmarks — 23 citations into it

Whom Anne Wu trusts overall

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

1. Diederik P. Kingma
2. Matt Post
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Ilya Sutskever
6. Alex Graves
7. Changhan Wang
8. Alexei Baevski
9. Jimmy Ba
10. Alex Krizhevsky

Who trusts Anne Wu overall

1. Changhan Wang
2. Ye Jia
3. Ankur Bapna
4. Ann Lee
5. Yun Tang
6. Juan Pino
7. Yu Zhang
8. Michelle Tadmor Ramanovich
9. Alec Radford
10. Zi-Hua Zhang

Papers from Anne Wu's perspective

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

Their papers

• VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation (2021) — 744 citations
• Fairseq S2T: Fast Speech-to-Text Modeling with Fairseq (2020) — 334 citations
• Large-Scale Self- and Semi-Supervised Learning for Speech Translation (2021) — 49 citations
• Self-Supervised Representations Improve End-to-End Speech Translation (2020) — 43 citations
• CoVoST 2: A Massively Multilingual Speech-to-Text Translation Corpus (2020) — 99 citations
• CoVoST 2 and Massively Multilingual Speech-to-Text Translation (2020) — 181 citations