Andrew M. Finch

Artificial Intelligence · 2005–2019

A researcher in the Science corpus: 3 papers; trusts 20 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 45 citations into it; #30,634 of 35,345 by trust here, #18,586 by citations
• Natural Language Processing — 44 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Model Architectures — 9 citations into it

Whom Andrew M. Finch trusts overall

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

1. Vladimir Naumovich Vapni
2. Dekang Lin
3. Mitchell P. Marcus
4. Matthew D. Zeiler
5. Yoshua Bengio
6. Dzmitry Bahdanau
7. John Blatz
8. Ilya Sutskever
9. Geoffrey E. Hinton
10. Kyunghyun Cho

Who trusts Andrew M. Finch overall

1. Dipanjan Das
2. Nitin Madnani
3. Stephen Wan
4. Noah A. Smith
5. Joel R. Tetreault
6. Mark Dras
7. Ion Androutsopoulos
8. Hamidreza Ghader

Papers from Andrew M. Finch's perspective

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

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

Their papers

• Findings of the Third Workshop on Neural Generation and Translation (2019) — 31 citations
• Neural Machine Translation with Supervised Attention (2016) — 162 citations
• Using Machine Translation Evaluation Techniques to Determine Sentence-level Semantic Equivalence (2005) — 114 citations