Victoria Langston

Artificial Intelligence · 2018–2025

A researcher in the Science corpus: 4 papers; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Victoria Langston trusts

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

  1. Kaiming He (in Computer Vision and Pattern Recognition)
  2. Geoffrey E. Hinton (in Artificial Intelligence)
  3. Oriol Vinyals (in Artificial Intelligence)
  4. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  5. Ilya Sutskever (in Artificial Intelligence)
  6. Jimmy Ba (in Artificial Intelligence)
  7. Diederik P. Kingma (in Artificial Intelligence)
  8. Yoshua Bengio (in Artificial Intelligence)
  9. Shaoqing Ren (in Computer Vision and Pattern Recognition)
  10. Abhinav Kumar Gupta (in Computer Vision and Pattern Recognition)

Papers from Victoria Langston's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Attention is All you Need (Neural Information Processing Systems)
  3. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  4. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  5. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
  6. Layer Normalization
  7. Dropout: a simple way to prevent neural networks from overfitting
  8. Human-level control through deep reinforcement learning
  9. Backpropagation Applied to Handwritten Zip Code Recognition
  10. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

Their papers