Payal Bajaj

Artificial Intelligence · 2016–2022

A researcher in the Science corpus: 8 papers; trusts 240 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Payal Bajaj trusts overall

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

  1. Geoffrey E. Hinton
  2. Yoshua Bengio
  3. Ilya Sutskever
  4. Diederik P. Kingma
  5. Kaiming He
  6. Alex Krizhevsky
  7. Yann LeCun
  8. Sepp Hochreiter
  9. Alex Graves
  10. J. Urgen Schmidhuber

Who trusts Payal Bajaj overall

  1. Sebastian Hofstätter
  2. Omar Khattab
  3. Niklas Muennighoff
  4. Jimmy J. Lin
  5. Sheng-Chieh Lin
  6. Johannes Welbl
  7. Shervin Minaee
  8. Linfeng Song
  9. Matei A. Zaharia
  10. Harshith Padigela

Papers from Payal Bajaj's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet classification with deep convolutional neural networks
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. ImageNet: A large-scale hierarchical image database
  7. Gradient-based learning applied to document recognition
  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