Joachim Daiber

Artificial Intelligence · 2013–2020

A researcher in the Science corpus: 2 papers; trusts 24 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Joachim Daiber trusts overall

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

  1. David N. Milne
  2. Danqi Chen
  3. Ian H. Witten
  4. Guillaume Lample
  5. Geoffrey E. Hinton
  6. Yiming Cui
  7. Yoshua Bengio
  8. Diederik P. Kingma
  9. Adam Roberts

Who trusts Joachim Daiber overall

  1. Petar Ristoski
  2. Michael Röder
  3. Yuncheng Li
  4. Sheng Zhang
  5. Anusri Pampari
  6. Yunseok Jang
  7. Yale Song
  8. Matthew E. Peters
  9. Pavlos Vougiouklis
  10. Weizhi Ma

Papers from Joachim Daiber's perspective

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

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

Their papers