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Max Welling: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Markus Weber, Max Welling, Pietro Perona
    Towards Automatic Discovery of Object Categories. [Citation Graph (0, 0)][DBLP]
    CVPR, 2000, pp:2101-0 [Conf]
  2. Markus Weber, Max Welling, Pietro Perona
    Unsupervised Learning of Models for Recognition. [Citation Graph (0, 0)][DBLP]
    ECCV (1), 2000, pp:18-32 [Conf]
  3. Markus Weber, Wolfgang Einhäuser, Max Welling, Pietro Perona
    Viewpoint-Invariant Learning and Detection of Human Heads. [Citation Graph (0, 0)][DBLP]
    FG, 2000, pp:20-27 [Conf]
  4. Max Welling, Geoffrey E. Hinton
    A New Learning Algorithm for Mean Field Boltzmann Machines. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:351-357 [Conf]
  5. Alex Holub, Max Welling, Pietro Perona
    Combining Generative Models and Fisher Kernels for Object Recognition. [Citation Graph (0, 0)][DBLP]
    ICCV, 2005, pp:136-143 [Conf]
  6. Peter V. Gehler, Alex Holub, Max Welling
    The rate adapting poisson model for information retrieval and object recognition. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:337-344 [Conf]
  7. Max Welling, Michal Rosen-Zvi, Yee Whye Teh
    Approximate inference by Markov chains on union spaces. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  8. Kenichi Kurihara, Max Welling, Yee Whye Teh
    Collapsed Variational Dirichlet Process Mixture Models. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:2796-2801 [Conf]
  9. Peter V. Gehler, Max Welling
    Products of Edge-perts. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  10. Geoffrey E. Hinton, Max Welling, Andriy Mnih
    Wormholes Improve Contrastive Divergence. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  11. Yee Whye Teh, Max Welling
    The Unified Propagation and Scaling Algorithm. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:953-960 [Conf]
  12. Max Welling, Felix V. Agakov, Christopher K. I. Williams
    Extreme Components Analysis. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  13. Max Welling, Geoffrey E. Hinton, Simon Osindero
    Learning Sparse Topographic Representations with Products of Student-t Distributions. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:1359-1366 [Conf]
  14. Max Welling, Michal Rosen-Zvi, Geoffrey E. Hinton
    Exponential Family Harmoniums with an Application to Information Retrieval. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  15. Max Welling, Yee Whye Teh
    Linear Response for Approximate Inference. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  16. Max Welling, Richard S. Zemel, Geoffrey E. Hinton
    Self Supervised Boosting. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:665-672 [Conf]
  17. Max Welling, Kenichi Kurihara
    Bayesian K-Means as a "Maximization-Expectation" Algorithm. [Citation Graph (0, 0)][DBLP]
    SDM, 2006, pp:- [Conf]
  18. Max Welling, Yee Whye Teh
    Belief Optimization for Binary Networks: A Stable Alternative to Loopy Belief Propagation. [Citation Graph (0, 0)][DBLP]
    UAI, 2001, pp:554-561 [Conf]
  19. Max Welling, Richard S. Zemel, Geoffrey E. Hinton
    Efficient Parametric Projection Pursuit Density Estimation. [Citation Graph (0, 0)][DBLP]
    UAI, 2003, pp:575-582 [Conf]
  20. Max Welling, Yee Whye Teh
    Approximate inference in Boltzmann machines. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 2003, v:143, n:1, pp:19-50 [Journal]
  21. Yee Whye Teh, Max Welling, Simon Osindero, Geoffrey E. Hinton
    Energy-Based Models for Sparse Overcomplete Representations. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2003, v:4, n:, pp:1235-1260 [Journal]
  22. Simon Osindero, Max Welling, Geoffrey E. Hinton
    Topographic Product Models Applied to Natural Scene Statistics. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2006, v:18, n:2, pp:381-414 [Journal]
  23. Max Welling, Yee Whye Teh
    Linear Response Algorithms for Approximate Inference in Graphical Models. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2004, v:16, n:1, pp:197-221 [Journal]
  24. Max Welling, Markus Weber
    A Constrained EM Algorithm for Independent Component Analysis. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2001, v:13, n:3, pp:677-689 [Journal]
  25. Max Welling, Markus Weber
    Positive tensor factorization. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 2001, v:22, n:12, pp:1255-1261 [Journal]
  26. Max Welling, Joseph J. Lim
    A Distributed Message Passing Algorithm for Sensor Localization. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2007, pp:767-775 [Conf]
  27. Sridevi Parise, Max Welling
    Bayesian Model Scoring in Markov Random Fields. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:1073-1080 [Conf]
  28. Yee Whye Teh, David Newman, Max Welling
    A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:1353-1360 [Conf]
  29. Kenichi Kurihara, Max Welling, Nikos A. Vlassis
    Accelerated Variational Dirichlet Process Mixtures. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:761-768 [Conf]
  30. Max Welling, Thomas P. Minka, Yee Whye Teh
    Structured Region Graphs: Morphing EP into GBP. [Citation Graph (0, 0)][DBLP]
    UAI, 2005, pp:609-614 [Conf]
  31. Max Welling
    On the Choice of Regions for Generalized Belief Propagation. [Citation Graph (0, 0)][DBLP]
    UAI, 2004, pp:585-592 [Conf]
  32. Ian R. Porteous, Alex Ihter, Padhraic Smyth, Max Welling
    Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]
  33. Max Welling, Sridevi Parise
    Bayesian Random Fields: The Bethe-Laplace Approximation. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]

  34. Multi-HDP: A Non Parametric Bayesian Model for Tensor Factorization. [Citation Graph (, )][DBLP]


  35. Bayesian Matrix Factorization with Side Information and Dirichlet Process Mixtures. [Citation Graph (, )][DBLP]


  36. Unsupervised learning of visual taxonomies. [Citation Graph (, )][DBLP]


  37. Incremental learning of nonparametric Bayesian mixture models. [Citation Graph (, )][DBLP]


  38. Memory bounded inference in topic models. [Citation Graph (, )][DBLP]


  39. Herding dynamical weights to learn. [Citation Graph (, )][DBLP]


  40. Dynamical Products of Experts for Modeling Financial Time Series. [Citation Graph (, )][DBLP]


  41. Bayesian Extreme Components Analysis. [Citation Graph (, )][DBLP]


  42. Fast collapsed gibbs sampling for latent dirichlet allocation. [Citation Graph (, )][DBLP]


  43. Base Station Localization in Search of Empty Spectrum Spaces in Cognitive Radio Networks. [Citation Graph (, )][DBLP]


  44. Collapsed Variational Inference for HDP. [Citation Graph (, )][DBLP]


  45. Distributed Inference for Latent Dirichlet Allocation. [Citation Graph (, )][DBLP]


  46. Infinite State Bayes-Nets for Structured Domains. [Citation Graph (, )][DBLP]


  47. Asynchronous Distributed Learning of Topic Models. [Citation Graph (, )][DBLP]


  48. Deterministic Latent Variable Models and Their Pitfalls. [Citation Graph (, )][DBLP]


  49. Hybrid Variational/Gibbs Collapsed Inference in Topic Models. [Citation Graph (, )][DBLP]


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