2008 |
46 | | Ian Porteous,
Evgeniy Bart,
Max Welling:
Multi-HDP: A Non Parametric Bayesian Model for Tensor Factorization.
AAAI 2008: 1487-1490 |
45 | EE | Ryan Gomes,
Max Welling,
Pietro Perona:
Incremental learning of nonparametric Bayesian mixture models.
CVPR 2008 |
44 | EE | Evgeniy Bart,
Ian Porteous,
Pietro Perona,
Max Welling:
Unsupervised learning of visual taxonomies.
CVPR 2008 |
43 | EE | Ryan Gomes,
Max Welling,
Pietro Perona:
Memory bounded inference in topic models.
ICML 2008: 344-351 |
42 | EE | Ian Porteous,
David Newman,
Alexander T. Ihler,
Arthur Asuncion,
Padhraic Smyth,
Max Welling:
Fast collapsed gibbs sampling for latent dirichlet allocation.
KDD 2008: 569-577 |
41 | EE | Arthur Asuncion,
Padhraic Smyth,
Max Welling:
Asynchronous Distributed Learning of Topic Models.
NIPS 2008: 81-88 |
40 | EE | Max Welling,
Chaitanya Chemudugunta,
Nathan Sutter:
Deterministic Latent Variable Models and Their Pitfalls.
SDM 2008: 196-207 |
39 | EE | Max Welling,
Yee Whye Teh,
Bert Kappen:
Hybrid Variational/Gibbs Collapsed Inference in Topic Models.
UAI 2008: 587-594 |
38 | EE | Alex Holub,
Max Welling,
Pietro Perona:
Hybrid Generative-Discriminative Visual Categorization.
International Journal of Computer Vision 77(1-3): 239-258 (2008) |
2007 |
37 | EE | Max Welling,
Joseph J. Lim:
A Distributed Message Passing Algorithm for Sensor Localization.
ICANN (1) 2007: 767-775 |
36 | EE | Kenichi Kurihara,
Max Welling,
Yee Whye Teh:
Collapsed Variational Dirichlet Process Mixture Models.
IJCAI 2007: 2796-2801 |
35 | EE | Yee Whye Teh,
Kenichi Kurihara,
Max Welling:
Collapsed Variational Inference for HDP.
NIPS 2007 |
34 | EE | David Newman,
Arthur Asuncion,
Padhraic Smyth,
Max Welling:
Distributed Inference for Latent Dirichlet Allocation.
NIPS 2007 |
33 | EE | Max Welling,
Ian Porteous,
Evgeniy Bart:
Infinite State Bayes-Nets for Structured Domains.
NIPS 2007 |
32 | EE | Max Welling:
Product of experts.
Scholarpedia 2(10): 3879 (2007) |
2006 |
31 | EE | Peter V. Gehler,
Alex Holub,
Max Welling:
The rate adapting poisson model for information retrieval and object recognition.
ICML 2006: 337-344 |
30 | EE | Sridevi Parise,
Max Welling:
Bayesian Model Scoring in Markov Random Fields.
NIPS 2006: 1073-1080 |
29 | EE | Yee Whye Teh,
David Newman,
Max Welling:
A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation.
NIPS 2006: 1353-1360 |
28 | EE | Kenichi Kurihara,
Max Welling,
Nikos A. Vlassis:
Accelerated Variational Dirichlet Process Mixtures.
NIPS 2006: 761-768 |
27 | EE | Max Welling,
Kenichi Kurihara:
Bayesian K-Means as a "Maximization-Expectation" Algorithm.
SDM 2006 |
26 | EE | Max Welling,
Sridevi Parise:
Bayesian Random Fields: The Bethe-Laplace Approximation.
UAI 2006 |
25 | EE | Ian Porteous,
Alex Ihter,
Padhraic Smyth,
Max Welling:
Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation.
UAI 2006 |
24 | EE | Simon Osindero,
Max Welling,
Geoffrey E. Hinton:
Topographic Product Models Applied to Natural Scene Statistics.
Neural Computation 18(2): 381-414 (2006) |
2005 |
23 | EE | Alex Holub,
Max Welling,
Pietro Perona:
Combining Generative Models and Fisher Kernels for Object Recognition.
ICCV 2005: 136-143 |
22 | EE | Peter V. Gehler,
Max Welling:
Products of Edge-perts.
NIPS 2005 |
21 | EE | Max Welling,
Thomas P. Minka,
Yee Whye Teh:
Structured Region Graphs: Morphing EP into GBP.
UAI 2005: 609-614 |
2004 |
20 | EE | Max Welling,
Michal Rosen-Zvi,
Yee Whye Teh:
Approximate inference by Markov chains on union spaces.
ICML 2004 |
19 | EE | Max Welling,
Michal Rosen-Zvi,
Geoffrey E. Hinton:
Exponential Family Harmoniums with an Application to Information Retrieval.
NIPS 2004 |
18 | EE | Max Welling:
On the Choice of Regions for Generalized Belief Propagation.
UAI 2004: 585-592 |
17 | EE | Max Welling,
Yee Whye Teh:
Linear Response Algorithms for Approximate Inference in Graphical Models.
Neural Computation 16(1): 197-221 (2004) |
2003 |
16 | EE | Max Welling,
Felix V. Agakov,
Christopher K. I. Williams:
Extreme Components Analysis.
NIPS 2003 |
15 | EE | Max Welling,
Yee Whye Teh:
Linear Response for Approximate Inference.
NIPS 2003 |
14 | EE | Geoffrey E. Hinton,
Max Welling,
Andriy Mnih:
Wormholes Improve Contrastive Divergence.
NIPS 2003 |
13 | | Max Welling,
Richard S. Zemel,
Geoffrey E. Hinton:
Efficient Parametric Projection Pursuit Density Estimation.
UAI 2003: 575-582 |
12 | EE | Max Welling,
Yee Whye Teh:
Approximate inference in Boltzmann machines.
Artif. Intell. 143(1): 19-50 (2003) |
11 | EE | Yee Whye Teh,
Max Welling,
Simon Osindero,
Geoffrey E. Hinton:
Energy-Based Models for Sparse Overcomplete Representations.
Journal of Machine Learning Research 4: 1235-1260 (2003) |
2002 |
10 | EE | Max Welling,
Geoffrey E. Hinton:
A New Learning Algorithm for Mean Field Boltzmann Machines.
ICANN 2002: 351-357 |
9 | EE | Max Welling,
Geoffrey E. Hinton,
Simon Osindero:
Learning Sparse Topographic Representations with Products of Student-t Distributions.
NIPS 2002: 1359-1366 |
8 | EE | Max Welling,
Richard S. Zemel,
Geoffrey E. Hinton:
Self Supervised Boosting.
NIPS 2002: 665-672 |
2001 |
7 | EE | Yee Whye Teh,
Max Welling:
The Unified Propagation and Scaling Algorithm.
NIPS 2001: 953-960 |
6 | EE | Max Welling,
Yee Whye Teh:
Belief Optimization for Binary Networks: A Stable Alternative to Loopy Belief Propagation.
UAI 2001: 554-561 |
5 | | Max Welling,
Markus Weber:
A Constrained EM Algorithm for Independent Component Analysis.
Neural Computation 13(3): 677-689 (2001) |
4 | EE | Max Welling,
Markus Weber:
Positive tensor factorization.
Pattern Recognition Letters 22(12): 1255-1261 (2001) |
2000 |
3 | EE | Markus Weber,
Max Welling,
Pietro Perona:
Towards Automatic Discovery of Object Categories.
CVPR 2000: 2101- |
2 | EE | Markus Weber,
Max Welling,
Pietro Perona:
Unsupervised Learning of Models for Recognition.
ECCV (1) 2000: 18-32 |
1 | EE | Markus Weber,
Wolfgang Einhäuser,
Max Welling,
Pietro Perona:
Viewpoint-Invariant Learning and Detection of Human Heads.
FG 2000: 20-27 |