Tabish Rashid

Reinforcement Learning · 2018–2023

A researcher in the Science corpus: 8 papers; trusts 190 researchers and is trusted by 71 researchers here, as inferred from the citation graph.

Subfields

Whom Tabish Rashid trusts overall

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

  1. Jakob N. Foerster
  2. Ming Tan
  3. Geoffrey E. Hinton
  4. Diederik P. Kingma
  5. Richard S. Sutton
  6. Yoshua Bengio
  7. Sepp Hochreiter
  8. J. Urgen Schmidhuber
  9. Alex Krizhevsky
  10. Radford M. Neal

Who trusts Tabish Rashid overall

  1. Christian Schröder de Witt
  2. Tonghan Wang
  3. Bei Peng
  4. Filippos Christianos
  5. Kyunghwan Son
  6. Wendelin Böhmer
  7. Jianhao Wang
  8. Shimon Whiteson
  9. Georgios Papoudakis
  10. Yaodong Yang

Papers from Tabish Rashid's perspective

Ordered by how strongly the researchers Tabish Rashid 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Long Short-Term Memory
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers