NIPS Proceedingsβ

Nicolas Heess

13 Papers

  • Distral: Robust multitask reinforcement learning (2017)
  • Filtering Variational Objectives (2017)
  • Imagination-Augmented Agents for Deep Reinforcement Learning (2017)
  • Learning Hierarchical Information Flow with Recurrent Neural Modules (2017)
  • Robust Imitation of Diverse Behaviors (2017)
  • Attend, Infer, Repeat: Fast Scene Understanding with Generative Models (2016)
  • Unsupervised Learning of 3D Structure from Images (2016)
  • Gradient Estimation Using Stochastic Computation Graphs (2015)
  • Learning Continuous Control Policies by Stochastic Value Gradients (2015)
  • Bayes-Adaptive Simulation-based Search with Value Function Approximation (2014)
  • Recurrent Models of Visual Attention (2014)
  • Learning to Pass Expectation Propagation Messages (2013)
  • Searching for objects driven by context (2012)