Filipe Wall Mutz

Reinforcement Learning · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 66 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Filipe Wall Mutz trusts overall

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

  1. J. Urgen Schmidhuber
  2. Richard S. Sutton
  3. Geoffrey E. Hinton
  4. Diederik P. Kingma
  5. Ronald J. Williams
  6. Jan Peters
  7. Andrew Barto
  8. Yoshua Bengio
  9. Radford M. Neal
  10. Alex Krizhevsky

Who trusts Filipe Wall Mutz overall

  1. Michael Janner
  2. J. Urgen Schmidhuber
  3. Sergey Levine
  4. Qiyang Li
  5. Benjamin Eysenbach
  6. Rupesh Kumar Srivastava
  7. Mengjiao Yang
  8. Dibya Ghosh

Papers from Filipe Wall Mutz's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Long Short-Term Memory
  5. Gradient-based learning applied to document recognition
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers