Maja Trebacz

Artificial Intelligence · 2021–2024

A researcher in the Science corpus: 3 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Maja Trebacz trusts overall

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

  1. Geoffrey E. Hinton
  2. Yoshua Bengio
  3. Diederik P. Kingma
  4. Alex Krizhevsky
  5. Alex Graves
  6. J. Urgen Schmidhuber
  7. Ethan Perez
  8. Ilya Sutskever
  9. Noam Shazeer
  10. Kaiming He

Papers from Maja Trebacz's perspective

Ordered by how strongly the researchers Maja Trebacz 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. Long Short-Term Memory
  3. ImageNet classification with deep convolutional neural networks
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
  7. Gradient-based learning applied to document recognition
  8. ImageNet: A large-scale hierarchical image database
  9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers