Utpal Kumar Sikdar

Artificial Intelligence · 2015–2017

A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 38 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 15 citations into it; #5,831 of 35,345 by trust here, #11,750 by citations
• Natural Language Processing — 11 citations into it; #1,274 of 5,688 by trust here, #3,235 by citations
• Communication — 6 citations into it
• Information Systems — 6 citations into it; #711 of 8,771 by trust here, #2,741 by citations
• Safety, Robustness & Interpretability — 5 citations into it

Whom Utpal Kumar Sikdar trusts overall

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

1. Zeerak Talat
2. Tomas Mikolov
3. Ellery Wulczyn
4. Thomas Davidson
5. Guang Xiang
6. Kai Chen
7. Dirk Hovy
8. Ilya Sutskever

Who trusts Utpal Kumar Sikdar overall

1. Ziqi Zhang
2. Antigoni-Maria Founta
3. Piyawat Lertvittayakumjorn
4. Kanika Narang
5. Rui Cao
6. Steven Zimmerman
7. Georgios K. Pitsilis
8. Ioannis Mollas
9. Tong Xiang
10. Wafa S. Alorainy

Papers from Utpal Kumar Sikdar's perspective

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

1. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
2. Natural Language Processing (Almost) from Scratch
3. Efficient Estimation of Word Representations in Vector Space
4. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet classification with deep convolutional neural networks
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. Long Short-Term Memory
9. Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter
10. Gradient-based learning applied to document recognition

Their papers

• The CHEMDNER corpus of chemicals and drugs and its annotation principles (2015) — 444 citations
• Using Convolutional Neural Networks to Classify Hate-Speech (2017) — 549 citations