Victoria Bi

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Victoria Bi trusts overall

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

  1. Ronald J. Williams
  2. Dzmitry Bahdanau
  3. Kyunghyun Cho
  4. Yoshua Bengio
  5. Jason Aaron Edward Weston

Papers from Victoria Bi's perspective

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

  1. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
  2. ImageNet classification with deep convolutional neural networks
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
  5. Long Short-Term Memory
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
  9. Gradient-based learning applied to document recognition
  10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers