Lucas Bandarkar

Artificial Intelligence · 2023

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Lucas Bandarkar trusts overall

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

  1. Jordan L. Boyd-Graber
  2. Taku Kudo
  3. Geoffrey E. Hinton
  4. Yoshua Bengio
  5. Nikita Nangia
  6. Diederik P. Kingma
  7. Emily M. Bender
  8. Ilya Sutskever
  9. Alexis Conneau
  10. Alex Krizhevsky

Papers from Lucas Bandarkar's perspective

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

  1. Attention is All you Need (Neural Information Processing Systems)
  2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  10. Gradient-based learning applied to document recognition

Their papers