Andrew Lefrancq

Reinforcement Learning · 2016–2018

A researcher in the Science corpus: 3 papers; trusts 8 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

Whom Andrew Lefrancq trusts overall

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

  1. Richard S. Sutton
  2. Ronald J. Williams
  3. Diederik P. Kingma

Who trusts Andrew Lefrancq overall

  1. Pieter Abbeel
  2. Tom Everitt
  3. Sergey Levine
  4. Nicolas Manfred Otto Heess
  5. Shane Legg

Papers from Andrew Lefrancq's perspective

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

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. ImageNet: A large-scale hierarchical image database
  3. Reinforcement Learning: An Introduction
  4. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
  5. Asynchronous Methods for Deep Reinforcement Learning
  6. Layer Normalization
  7. Trust Region Policy Optimization (International Conference on Machine Learning)
  8. The Arcade Learning Environment: An Evaluation Platform for General Agents
  9. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
  10. Intriguing properties of neural networks

Their papers