NIPS Proceedingsβ

Justin Domke

8 Papers

  • Importance Weighting and Variational Inference (2018)
  • Using Large Ensembles of Control Variates for Variational Inference (2018)
  • Maximum Likelihood Learning With Arbitrary Treewidth via Fast-Mixing Parameter Sets (2015)
  • Reflection, Refraction, and Hamiltonian Monte Carlo (2015)
  • Projecting Markov Random Field Parameters for Fast Mixing (2014)
  • Projecting Ising Model Parameters for Fast Mixing (2013)
  • Structured Learning via Logistic Regression (2013)
  • Implicit Differentiation by Perturbation (2010)