Steve Durairaj Swamy

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 30 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it; #20,208 of 35,345 by trust here, #28,481 by citations
• Natural Language Processing — 25 citations into it; #3,433 of 5,688 by trust here, #4,983 by citations
• Information Systems — 11 citations into it
• Communication — 7 citations into it
• Social Psychology — 6 citations into it
• AI Ethics, Fairness & Society — 5 citations into it

Whom Steve Durairaj Swamy trusts overall

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

1. Zeerak Talat
2. Diederik P. Kingma
3. Marcos Zampieri
4. Sepp Hochreiter
5. Thomas Davidson
6. Jeffrey Pennington
7. Mladen Karan
8. Jacob Devlin
9. Jimmy Ba
10. J. Urgen Schmidhuber

Who trusts Steve Durairaj Swamy overall

1. Endang Wahyu Pamungkas
2. Valerio Basile
3. Svetlana Kiritchenko
4. Tommaso Caselli
5. Jing Xu
6. Isar Nejadgholi
7. Viviana Patti
8. Da Ju

Papers from Steve Durairaj Swamy's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Long Short-Term Memory
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet classification with deep convolutional neural networks
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. ImageNet: A large-scale hierarchical image database
9. GloVe: Global Vectors for Word Representation
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Studying Generalisability across Abusive Language Detection Datasets (2019) — 105 citations