Rachael Tatman

Artificial Intelligence · 2017–2021

A researcher in the Science corpus: 3 papers; trusts 12 researchers and is trusted by 55 researchers here, as inferred from the citation graph.

Subfields

Whom Rachael Tatman trusts overall

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

  1. Sharon Goldwater
  2. Dan Jurafsky
  3. Antonio Torralba
  4. Dirk Hovy
  5. Carla Lopes
  6. Meghan Sumner
  7. Wayne Xiong
  8. Christopher D. Manning
  9. Hank Liao
  10. Paul P. G. Boersma

Who trusts Rachael Tatman overall

  1. Josh Meyer
  2. David Bamman
  3. Rachel Rudinger
  4. Shrimai Prabhumoye
  5. Chris Sweeney
  6. Lindy Rauchenstein
  7. Rowan Zellers
  8. Ryan Shaun Joazeiro de Baker
  9. Lucie Flekova
  10. Emily M. Bender

Papers from Rachael Tatman's perspective

Ordered by how strongly the researchers Rachael Tatman 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. ImageNet classification with deep convolutional neural networks
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. ImageNet: A large-scale hierarchical image database
  10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers