Yu. V. Gorishniy

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

Whom Yu. V. Gorishniy trusts overall

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

  1. Kaiming He
  2. Diederik P. Kingma
  3. Noam Shazeer
  4. Geoffrey E. Hinton
  5. Jimmy Ba
  6. X. Zhang
  7. Alex Krizhevsky
  8. Yoshua Bengio
  9. Shaoqing Ren
  10. Ilya Sutskever

Who trusts Yu. V. Gorishniy overall

  1. Léo Grinsztajn
  2. C. Yuhua
  3. Edouard Oyallon
  4. Akim Kotelnikov
  5. Songqiao Han
  6. Noah Hollmann
  7. Gaël Varoquaux
  8. Duncan C. McElfresh
  9. Chen Yuhua
  10. Dmitry Baranchuk

Papers from Yu. V. Gorishniy's perspective

Ordered by how strongly the researchers Yu. V. Gorishniy 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers