Dipankar Ray

Artificial Intelligence · 2012–2022

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Dipankar Ray trusts

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

  1. Yejin Choi (in Artificial Intelligence)
  2. Noah A. Smith (in Artificial Intelligence)
  3. J. Langford (in Management Science and Operations Research)
  4. Lihong Li (in Management Science and Operations Research)
  5. Maarten Sap (in Artificial Intelligence)
  6. Tom L. Burr (in Artificial Intelligence)
  7. Stephen W. Carden (in Reinforcement Learning)
  8. Judea Pearl (in Statistics and Probability)
  9. Zeerak Talat (in Artificial Intelligence)

Who trusts Dipankar Ray

  1. Lihong Li (in Reinforcement Learning)
  2. Thorsten Joachims (in Artificial Intelligence)
  3. Ziyang Tang (in Reinforcement Learning)
  4. Adith Swaminathan (in Artificial Intelligence)

Papers from Dipankar Ray's perspective

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

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

Their papers