Ashutosh Choudhary

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 23 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 22 citations into it; #13,309 of 35,345 by trust here, #16,771 by citations
• Natural Language Processing — 22 citations into it; #2,499 of 5,688 by trust here, #3,421 by citations
• Large Language Models — 8 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it

Whom Ashutosh Choudhary trusts overall

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

1. Diederik P. Kingma
2. Alec Radford
3. Sosuke Kobayashi
4. Geoffrey E. Hinton
5. Rico Sennrich
6. Jimmy Ba
7. Yoshua Bengio
8. Ilya Sutskever
9. Jacob Devlin
10. Alex Krizhevsky

Who trusts Ashutosh Choudhary overall

1. Timo Schick
2. Omid Kashefi
3. Bohan Li
4. Azal Ahmad Khan
5. Nathan Ng
6. Junnan Li
7. Silei Xu
8. Jiaao Chen
9. Steven Y. Feng
10. Michael A. Hedderich

Papers from Ashutosh Choudhary's perspective

Ordered by how strongly the researchers Ashutosh Choudhary 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. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Data Augmentation using Pre-trained Transformer Models (2020) — 411 citations