Timo Möller

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Timo Möller trusts overall

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

  1. Jörg Tiedemann
  2. Alan Akbik
  3. Jeremy Howard
  4. Michael Wiegand
  5. Jacob Devlin

Papers from Timo Möller's perspective

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

  1. Attention is All you Need (Neural Information Processing Systems)
  2. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  3. Long Short-Term Memory
  4. ImageNet classification with deep convolutional neural networks
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Deep Contextualized Word Representations (North American Chapter of the Association for Computational Linguistics)
  7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  8. RoBERTa: A Robustly Optimized BERT Pretraining Approach (arXiv.org)
  9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  10. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)

Their papers