NIPS Proceedingsβ

Erik B. Sudderth

16 Papers

  • Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential Data (2012)
  • From Deformations to Parts: Motion-based Segmentation of 3D Objects (2012)
  • Minimization of Continuous Bethe Approximations: A Positive Variation (2012)
  • Truly Nonparametric Online Variational Inference for Hierarchical Dirichlet Processes (2012)
  • Spatial distance dependent Chinese restaurant processes for image segmentation (2011)
  • The Doubly Correlated Nonparametric Topic Model (2011)
  • Global seismic monitoring as probabilistic inference (2010)
  • Layered image motion with explicit occlusions, temporal consistency, and depth ordering (2010)
  • Sharing Features among Dynamical Systems with Beta Processes (2009)
  • Nonparametric Bayesian Learning of Switching Linear Dynamical Systems (2008)
  • Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes (2008)
  • Loop Series and Bethe Variational Bounds in Attractive Graphical Models (2007)
  • Describing Visual Scenes using Transformed Dirichlet Processes (2005)
  • Distributed Occlusion Reasoning for Tracking with Nonparametric Belief Propagation (2004)
  • Efficient Multiscale Sampling from Products of Gaussian Mixtures (2003)
  • Tree-Based Modeling and Estimation of Gaussian Processes on Graphs with Cycles (2000)