Victor Gabillon

Reinforcement Learning · 2011–2015

A researcher in the Science corpus: 5 papers; trusts 24 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

Whom Victor Gabillon trusts overall

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

  1. R´emi Munos
  2. Dimitri P. Bertsekas
  3. Jean-Yves Audibert
  4. Michail G. Lagoudakis
  5. Sébastien Bubeck
  6. Nikolaus Hansen
  7. Andreas Maurer
  8. Richard S. Sutton
  9. Csaba Szepesvari
  10. Volodymyr Mnih

Who trusts Victor Gabillon overall

  1. Yutian Chen
  2. Aviv Tamar
  3. Kevin G. Jamieson
  4. Bobak Shahriari
  5. Emilie Kaufmann
  6. Stefan Elfwing
  7. Bruno Scherrer
  8. Matthew D. Hoffman
  9. Matthew W. Hoffman
  10. Sébastien Bubeck

Papers from Victor Gabillon's perspective

Ordered by how strongly the researchers Victor Gabillon 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. Reinforcement Learning: An Introduction
  4. Gradient-based learning applied to document recognition
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. ImageNet: A large-scale hierarchical image database
  7. Learning Multiple Layers of Features from Tiny Images
  8. Asynchronous Methods for Deep Reinforcement Learning
  9. Long Short-Term Memory
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers