NIPS Proceedingsβ

Pieter Abbeel

17 Papers

  • Backprop KF: Learning Discriminative Deterministic State Estimators (2016)
  • Combinatorial Energy Learning for Image Segmentation (2016)
  • Cooperative Inverse Reinforcement Learning (2016)
  • InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets (2016)
  • Learning to Poke by Poking: Experiential Learning of Intuitive Physics (2016)
  • Value Iteration Networks (2016)
  • VIME: Variational Information Maximizing Exploration (2016)
  • Gradient Estimation Using Stochastic Computation Graphs (2015)
  • Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics (2014)
  • Risk Aversion in Markov Decision Processes via Near Optimal Chernoff Bounds (2012)
  • On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient (2010)
  • Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion (2007)
  • An Application of Reinforcement Learning to Aerobatic Helicopter Flight (2006)
  • Max-margin classification of incomplete data (2006)
  • Learning vehicular dynamics, with application to modeling helicopters (2005)
  • Learning first-order Markov models for control (2004)
  • Link Prediction in Relational Data (2003)