NIPS Proceedingsβ

Raquel Urtasun

18 Papers

  • Neural Guided Constraint Logic Programming for Program Synthesis (2018)
  • Few-Shot Learning Through an Information Retrieval Lens (2017)
  • The Reversible Residual Network: Backpropagation Without Storing Activations (2017)
  • Learning Deep Parsimonious Representations (2016)
  • Proximal Deep Structured Models (2016)
  • Understanding the Effective Receptive Field in Deep Convolutional Neural Networks (2016)
  • 3D Object Proposals for Accurate Object Class Detection (2015)
  • Skip-Thought Vectors (2015)
  • Efficient Inference of Continuous Markov Random Fields with Polynomial Potentials (2014)
  • Message Passing Inference for Large Scale Graphical Models with High Order Potentials (2014)
  • Latent Structured Active Learning (2013)
  • 3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model (2012)
  • Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins (2012)
  • Joint 3D Estimation of Objects and Scene Layout (2011)
  • Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities (2011)
  • A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction (2010)
  • Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation (2010)
  • Sparse Coding for Learning Interpretable Spatio-Temporal Primitives (2010)