Alexander Gelbukh

Artificial Intelligence · 2001–2020

A researcher in the Science corpus: 16 papers; trusts 172 researchers and is trusted by 62 researchers here, as inferred from the citation graph.

Subfields

Whom Alexander Gelbukh trusts overall

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

  1. Soujanya Poria
  2. Tomas Mikolov
  3. Yoon Kim
  4. Erik Cambria
  5. Diederik P. Kingma
  6. Geoffrey E. Hinton
  7. Yoshua Bengio
  8. Ilya Sutskever
  9. Christopher D. Manning
  10. Alex Krizhevsky

Who trusts Alexander Gelbukh overall

  1. Soujanya Poria
  2. Erik Cambria
  3. Devamanyu Hazarika
  4. Ringki Das
  5. Navonil Majumder
  6. Amir Zadeh
  7. Endang Wahyu Pamungkas
  8. Vukosi Marivate
  9. Ramakanth Pasunuru
  10. Tom Young

Papers from Alexander Gelbukh's perspective

Ordered by how strongly the researchers Alexander Gelbukh 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. Long Short-Term Memory
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers