Aditya Thyagarajan

Artificial Intelligence · 2016

A researcher in the Science corpus: 1 paper; trusts 15 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it; #7,700 of 35,345 by trust here, #15,236 by citations
• Natural Language Processing — 16 citations into it; #1,628 of 5,688 by trust here, #3,190 by citations
• Computer Vision and Pattern Recognition — 7 citations into it; #5,614 of 21,575 by trust here, #10,334 by citations
• Model Architectures — 7 citations into it
• Representation & Self-Supervised Learning — 6 citations into it; #954 of 3,145 by trust here, #1,885 by citations

Whom Aditya Thyagarajan trusts overall

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

1. Ilya Sutskever
2. Tomas Mikolov
3. Yann LeCun
4. Junbo Jake Zhao
5. Yoshua Bengio
6. Geoffrey E. Hinton
7. Oriol Vinyals
8. Alex Graves
9. Quoc V. Le
10. Eneko Agirre

Who trusts Aditya Thyagarajan overall

1. Juri Opitz
2. Zhiquan Ye
3. Mathijs Mul
4. Vukosi Marivate
5. Mahmut Kaya
6. Shervin Minaee
7. Dallas Card
8. Qi Liu
9. Zihang Chen
10. Praveen Kumar Badimala Giridhara

Papers from Aditya Thyagarajan's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Attention is All you Need (Neural Information Processing Systems)
5. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
9. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Siamese Recurrent Architectures for Learning Sentence Similarity (2016) — 992 citations