Kaushik Chakrabarti

Artificial Intelligence · 2001–2019

A researcher in the Science corpus: 8 papers; trusts 26 researchers and is trusted by 34 researchers here, as inferred from the citation graph.

Subfields

Whom Kaushik Chakrabarti trusts overall

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

  1. Jerome H. Friedman
  2. Jianhua Lin
  3. Michael J. Cafarella
  4. Byoung-Kee Yi
  5. Alon Y. Halevy
  6. Muthu Dayalan
  7. Jonathan Cohen
  8. Sam T. Roweis
  9. Taher H. Haveliwala
  10. Bahman Bahmani

Who trusts Kaushik Chakrabarti overall

  1. Eamonn J. Keogh
  2. Jessica Lin
  3. Yunyue Zhu
  4. Tak-Chung Fu
  5. Pavel Berkhin
  6. Chotirat (Ann) Ratanamahatana
  7. Michail Vlachos
  8. Lei Chen
  9. Dennis E. Shasha
  10. Leyla Bilge

Papers from Kaushik Chakrabarti's perspective

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

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

Their papers