Travis Armstrong

Artificial Intelligence · 2020–2025

A researcher in the Science corpus: 4 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Travis Armstrong trusts

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

  1. Dean A. Pomerleau (in Reinforcement Learning)
  2. Sergey Levine (in Artificial Intelligence)
  3. Kaiming He (in Computer Vision and Pattern Recognition)
  4. Shaoqing Ren (in Computer Vision and Pattern Recognition)
  5. Pieter Abbeel (in Artificial Intelligence)
  6. X. Zhang (in Computer Vision and Pattern Recognition)
  7. Corey Lynch (in Reinforcement Learning)

Papers from Travis Armstrong's perspective

Ordered by how strongly the researchers Travis Armstrong 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. Attention is All you Need (Neural Information Processing Systems)
  3. ImageNet: A large-scale hierarchical image database
  4. Et al
  5. Rectified Linear Units Improve Restricted Boltzmann Machines
  6. ImageNet classification with deep convolutional neural networks
  7. Multitask Learning
  8. Fully convolutional networks for semantic segmentation
  9. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (International Conference on Learning Representations)
  10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers