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Neal, R. M. (1993). Probabilistic Inference Using Markov Chain Monte Carlo Methods (Technical Report) . Department of Computer Science, University of Toronto.

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Inferring State Sequences for Non-linear - Systems With Embedded   Self-citation (Neal)   (Correct)

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Neal, R. M. (1993) Probabilistic Inference Using Markov Chain Monte Carlo Methods, Technical Report CRG-TR-93-1, Dept. of Computer Science, University of Toronto, 144 pages. Available from http://www.cs.utoronto.ca/#radford.


Inferring State Sequences for Non-linear - Systems With Embedded   Self-citation (Neal)   (Correct)

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Neal, R. M. (1993) Probabilistic Inference Using Markov Chain Monte Carlo Methods, Technical Report CRG-TR-93-1, Dept. of Computer Science, University of Toronto, 144 pages. Available from http://www.cs.utoronto.ca/#radford.


Inferring State Sequences for Non-linear - Systems With Embedded (2003)   Self-citation (Neal)   (Correct)

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Neal, R. M. (1993) Probabilistic Inference Using Markov Chain Monte Carlo Methods, Technical Report CRG-TR-93-1, Dept. of Computer Science, University of Toronto, 144 pages. Available from http://www.cs.utoronto.ca/#radford.


Efficient Feature Construction by Meta Learning - Guiding the .. - Mierswa, Wurst (2005)   (Correct)

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Neal, R. M. (1993). Probabilistic Inference Using Markov Chain Monte Carlo Methods (Technical Report) . Department of Computer Science, University of Toronto.


A Non-Parametric Bayesian Approach to Spike Sorting - Frank Wood Sharon (2006)   (Correct)

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R. M. Neal, "Probabilistic inference using Markov chain Monte Carlo methods," University of Toronto, Tech. Rep. CRG-TR-93-1, 1993.


Variational methods for the Dirichlet process - Blei, Jordan (2004)   (1 citation)  (Correct)

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Neal, R. (1993). Probabilistic inference using Markov chain Monte Carlo methods (Technical Report CRG-TR-93-1). Department of Computer Science, University of Toronto.


Fields of Experts: A Framework for Learning Image Priors - Roth, Black (2005)   (Correct)

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R. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, Dept. of Computer Science, University of Toronto, 1993.


The Prior-Predictive Value: - Paradigm Of Nasty   (Correct)

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R. Neal, "Probabilistic inference using markov chain monte carlo methods," Dept. of Computer Science, University Toronto, 1993.


On Evidence Weighted Mixture Classification - Everson, Krzanowski, Bailey..   (Correct)

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R.M. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, Dept. of Computer Science, University of Toronto, 1993.


Graphical Models for Statistical Inference and Data.. - Ihler, Kirshner.. (2005)   (Correct)

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R. M. Neal, Probabilistic inference using Markov Chain Monte Carlo methods, Tech. Rep. CRG-TR-93-1, Dept. of Comp. Sci., Univ. of Toronto (1993).


Bayesian Learning in Undirected Graphical Models.. - Murray, Ghahramani (2004)   (3 citations)  (Correct)

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Radford M. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical report, Department of Computer Science, University of Toronto, September 1993.


Efficient Feature Construction by Meta Learning - Guiding the .. - Mierswa, Wurst (2005)   (Correct)

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Neal, R. M. (1993). Probabilistic Inference Using Markov Chain Monte Carlo Methods (Technical Report) . Department of Computer Science, University of Toronto.


Probabilistic Independence Networks for Hidden Markov.. - Smyth, Heckerman, al. (1996)   (91 citations)  (Correct)

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Neal, R. 1993. Probabilistic inference using Markov chain Monte Carlo methods. CRGTR -93-1, Department of Computer Science, University of Toronto.


World Independent Context Pair Classification Model for . . . - Niu, Al. (2005)   (Correct)

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Neal, R.M. 1993. Probabilistic Inference Using Markov Chain Monte Carlo Methods. Technical Report, Univ. of Toronto.


Learning Dynamic Bayesian Networks - Zoubin Ghahramani Department (1997)   (39 citations)  (Correct)

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R. M. Neal. Probabilistic inference using Markov chain monte carlo methods. Technical Report CRG-TR-93-1, Department of Computer Science, University of Toronto, 1993.


Fields of Experts: A Framework for Learning Image Priors - Roth, Black (2005)   (Correct)

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R. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, Dept. of Computer Science, University of Toronto, 1993.


Reinforcement Learning for Factored Markov Decision Processes - Sallans (2002)   (Correct)

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Neal, R. M. (1993). Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, Department of Computer Science, University of Toronto.


Bayesian Learning in Nonlinear State-Space Models - Andrews   (Correct)

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Neal, R. M. (1993), Probabilistic inference using markov chain monte carlo methods, Technical report, University of Toronto.


The Prior-Predictive Value: A Paradigm of Nasty.. - von der Linden.. (1999)   (Correct)

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R. Neal, "Probabilistic inference using markov chain monte carlo methods," Dept. of Computer Science, University Toronto, 1993.


Distributed Clustering with Limited Knowledge Sharing - Ghosh, Merugu   (Correct)

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R. M. Neal. Probabilistic inference using Markov Chain Monte Carlo methods. Technical Report CRG-TR-93-1, Dept. of Computer Science, Univ. of Toronto, 1993.


Bayesian Learning in Undirected Graphical Models.. - Murray, Ghahramani (2004)   (3 citations)  (Correct)

No context found.

Radford M. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical report, Department of Computer Science, University of Toronto, September 1993.


Linearly scalable hybrid Monte Carlo method for.. - Hampton, Izaguirre (2002)   (Correct)

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R. M. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, university of Toronto, 1993. papers available from http://www.cs.toronto.edu/radford/papers-online.html.


The design and implementation of a Bayesian CAD modeler for - Robotic Applications..   (Correct)

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Neal, R. M. (1993). Probabilistic inference using Markov Chain Monte Carlo methods. Research Report CRG-TR-93-1, Dept. of Computer Science, University of Toronto.


A Probabilistic Approach to Privacy-sensitive Distributed.. - Srujana Merugu And (2003)   (1 citation)  (Correct)

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R. M. Neal. Probabilistic inference using Markov Chain Monte Carlo methods. Technical Report CRG-TR-93-1, Dept. of Computer Science, Univ. of Toronto, 1993.


Improved Sampling of Configuration Space of Biomolecules Using.. - Hampton (2004)   (Correct)

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R. M. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, University of Toronto, 1993.


Shadow Hybrid Monte Carlo: An Efficient Propagator in Phase .. - Izaguirre, Hampton (2004)   (Correct)

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R. M. Neal, Probabilistic inference using Markov chain Monte Carlo methods, Tech. Rep. CRG-TR-93-1, University of Toronto (1993).


Privacy-preserving Distributed Clustering using Generative.. - Srujana Merugu And (2003)   (4 citations)  (Correct)

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R. M. Neal. Probabilistic inference using Markov Chain Monte Carlo methods. Technical Report CRG-TR-93-1, Dept. of Computer Science, University of Toronto, 1993.


Regularized Greedy Importance Sampling - Finnegan Southey Dale   (Correct)

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R. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Tech report, 1993.


Bayesian Model Averaging Across Model Spaces via Compact Encoding - Yin, Davidson   (Correct)

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Neal, R., Probabilistic Inference Using Markov Chain Monte Carlo Method, Technical Report CRG-TR-93-1, Department of Computer Science University of Toronto, 1993.


Message Length Estimators, Probabilistic Sampling and Optimal.. - Davidson, Yin   (Correct)

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Neal, R., Probabilistic Inference Using Markov Chain Monte Carlo Method, Technical Report CRG-TR-93-1, Department of Computer Science University of Toronto, 1993.


A Probabilistic Approach to Privacy-sensitive Distributed.. - Srujana Merugu And (2003)   (1 citation)  (Correct)

No context found.

R. M. Neal. Probabilistic inference using Markov Chain Monte Carlo methods. Technical Report CRG-TR-93-1, Dept. of Computer Science, Univ. of Toronto, 1993.


An MCMC-based Particle Filter - For Tracking Multiple   (Correct)

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Neal, R.: Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, Dept. of Computer Science, University of Toronto (1993)


Gaussian Processes for Machine Learning - Seeger (2004)   (Correct)

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R. M. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, University of Toronto, 1993. See www.cs.toronto.edu/~radford.


Model Selection for Support Vector Machine Classification - Gold, Sollich (2002)   (Correct)

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R M Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, University of Toronto, 1993.


An MCMC-based Particle Filter For Tracking Multiple.. - Khan, Balch, Dellaert (2003)   (1 citation)  (Correct)

No context found.

R.M. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, Dept. of Computer Science, University of Toronto, 1993.


Regularized Greedy Importance Sampling - Finnegan Southey Dale   (Correct)

No context found.

R. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Tech report, 1993.


A Mode-Hopping MCMC sampler - Sminchisescu, Welling, Hinton (2003)   (Correct)

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R. Neal. Probabilistic Inference Using Markov Chain Monte Carlo. Technical Report CRGTR -93-1, University of Toronto, 1993.


Approximate Learning and Inference for Tracking with.. - Zajdel, Kröse   (Correct)

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Radford M. Neal. Probabilistic inference using Markov Chain Monte Carlo methods. Technical Report CRGTR -93-1, University of Toronto, 1993.


Aircraft Recognition from Features Extracted from Measured and.. - Zwart (2003)   (Correct)

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Radford M. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, Dept. of Computer Science, University of Toronto, September 1993.


Probabilistic Inference of Speech Signals from - Phaseless Spectrograms Kannan (2003)   (Correct)

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Neal, R. M, Probabilistic inference using Markov chain Monte Carlo Methods, University of Toronto Technical Report 1993


Mcmc Methods For Discrete Source Separation - Stephane Senecal Pierre-Olivier (2000)   (1 citation)  (Correct)

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R. M. Neal, "Probabilistic inference using Markov chain Monte Carlo methods," Dpt. of Computer Science, University of Toronto, CRG-TR-93-1, 1993.


Three-Dimensional Reconstruction of Fire from Images - Hasinoff (2002)   (1 citation)  (Correct)

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R. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, University of Toronto, 1993.


Bayesian Gaussian Process Models: PAC-Bayesian Generalisation.. - Seeger (2003)   (3 citations)  (Correct)

No context found.

R. M. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical report, University of Toronto, 1993.


Bayesian Kernel Methods - Smola, Schölkopf (2003)   (Correct)

No context found.

Radford M. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical report, Dept. of Computer Science, University of Toronto, 1993. CRGTR -93-1.


Advances in Algorithms for Inference and Learning in Complex.. - Frey, Jojic (2002)   (1 citation)  (Correct)

No context found.

R. M. Neal. Probabilistic inference using Markov chain Monte Carlo methods. University of Toronto Technical Report, 1993.


Bayesian Separation Of Discrete Sources Via Gibbs Sampling - Stephane Senecal And (2000)   (Correct)

No context found.

Radford M. Neal. "Probabilistic Inference Using Markov Chain Monte Carlo Methods". Technical Report CRG-TR-93-1, Dpt. of Computer Science, University of Toronto.


Sample Propagation - Paskin (2003)   (Correct)

No context found.

R. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, University of Toronto, 1993.


Bayesian Model Averaging Across Model Spaces via Compact Encoding - Ke Yin Ian   (Correct)

No context found.

R. Neal, Probabilistic Inference Using Markov Chain Monte Carlo Method, Technical Report CRG-TR-93-1, Department of Computer Science University of Toronto, 1993.


Probabilistic Inference of Speech Signals from - Phaseless Spectrograms Kannan (2003)   (Correct)

No context found.

Neal, R. M, Probabilistic inference using Markov chain Monte Carlo Methods, University of Toronto Technical Report 1993


Sample Propagation - Paskin (2003)   (Correct)

No context found.

R. Neal. Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, University of Toronto, 1993.

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