NIPS Proceedingsβ

Stefano Ermon

16 Papers

  • Amortized Inference Regularization (2018)
  • Bias and Generalization in Deep Generative Models: An Empirical Study (2018)
  • Constructing Unrestricted Adversarial Examples with Generative Models (2018)
  • Multi-Agent Generative Adversarial Imitation Learning (2018)
  • Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance (2018)
  • Streamlining Variational Inference for Constraint Satisfaction Problems (2018)
  • A-NICE-MC: Adversarial Training for MCMC (2017)
  • InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations (2017)
  • Neural Variational Inference and Learning in Undirected Graphical Models (2017)
  • Adaptive Concentration Inequalities for Sequential Decision Problems (2016)
  • Generative Adversarial Imitation Learning (2016)
  • Solving Marginal MAP Problems with NP Oracles and Parity Constraints (2016)
  • Variational Bayes on Monte Carlo Steroids (2016)
  • Embed and Project: Discrete Sampling with Universal Hashing (2013)
  • Density Propagation and Improved Bounds on the Partition Function (2012)
  • Accelerated Adaptive Markov Chain for Partition Function Computation (2011)