NIPS Proceedingsβ

José Miguel Hernández-Lobato

10 Papers

  • A Model to Search for Synthesizable Molecules (2019)
  • Bayesian Batch Active Learning as Sparse Subset Approximation (2019)
  • Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model (2019)
  • Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning (2019)
  • Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo (2018)
  • Stochastic Expectation Propagation (2015)
  • Gaussian Process Volatility Model (2014)
  • Predictive Entropy Search for Efficient Global Optimization of Black-box Functions (2014)
  • Gaussian Process Conditional Copulas with Applications to Financial Time Series (2013)
  • Learning Feature Selection Dependencies in Multi-task Learning (2013)