Thomas Hubert

Artificial Intelligence · 2017–2022

A researcher in the Science corpus: 7 papers; trusts 7 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

Whom Thomas Hubert trusts overall

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

  1. David Silver
  2. Richard S. Sutton
  3. Rémi Coulom
  4. Kaiming He
  5. Geoffrey E. Hinton
  6. T. Marsland
  7. Diederik P. Kingma
  8. J. Urgen Schmidhuber
  9. Ilya Sutskever
  10. Martin L. Puterman

Who trusts Thomas Hubert overall

  1. Danijar Hafner
  2. Yuxi Li
  3. Hengyuan Hu
  4. Jimmy Ba
  5. Adam Lerer
  6. Sergey Levine
  7. Matteo Hessel
  8. Albert Qiaochu Jiang
  9. Noam Brown
  10. Jieyi Long

Papers from Thomas Hubert's perspective

Ordered by how strongly the researchers Thomas Hubert 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. ImageNet classification with deep convolutional neural networks
  3. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Long Short-Term Memory
  6. Gradient-based learning applied to document recognition
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Asynchronous Methods for Deep Reinforcement Learning
  9. Human-level control through deep reinforcement learning
  10. ImageNet: A large-scale hierarchical image database

Their papers