Bayesian Research Kitchen Workshop (BARK), Grasmere 2008

Bayesian Research Kitchen Workshop (BARK), Grasmere 2008

13 Videos · Sep 6, 2008

About

Motivation\ The main aim of this workshop is to allow leading Bayesian researchers in machine learning to get together presenting their latest ideas and discussing future directions.

Themes\ * Incorporating Complex Prior Knowledge in Bayesian inference, for example mechanistic models (such as differential equations) or knowledge transfered from other related situations (e.g. hierarchical Dirichlet Processes). * Model mismatch: the Bayesian lynch pin is that the model is correct, but it rarely is. * Approximation techniques: how should we do Bayesian inference in practice. Sampling, variational, Laplace or something else? * Your pet Bayesian issue here.

Visit the Workshop website here.

Videos

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57:29

Negotiated Interaction : Iterative Inference and Feedback of Intention in HCI

Roderick Murray-Smith

Oct 9, 2008

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3555 views

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50:22

Probabilistic models for ranking and information extraction

Ed Snelson

Oct 9, 2008

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3209 views

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47:27

Bayesian learning of sparse factor loadings

Magnus Rattray

Oct 9, 2008

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5294 views

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51:02

Latent Force Models with Gaussian Processes

Neil D. Lawrence

Oct 9, 2008

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4972 views

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42:22

On the relation between Bayesian inference and certain solvable problems of stoc...

Manfred Opper

Oct 9, 2008

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4672 views

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01:00:21

Well-known shortcomings, advantages and computational challenges in Bayesian mod...

Ole Winther

Oct 9, 2008

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4521 views

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01:00:37

Should all Machine Learning be Bayesian? Should all Bayesian models be non-param...

Zoubin Ghahramani

Oct 9, 2008

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27816 views

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01:06:35

Multi-task Learning with Gaussian Processes

Chris Williams

Oct 9, 2008

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6299 views

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54:54

Variational Model Selection for Sparse Gaussian Process Regression

Michalis K. Titsias

Oct 9, 2008

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6201 views

Draft
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01:07:09

Bayeswatch

Amos Storkey

Feb 18, 2024

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8 views

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44:49

Covariance functions and Bayes errors for GP regression on random graphs

Peter Sollich

Oct 9, 2008

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3820 views

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10:51

Introduction to BARK 2008

Neil D. Lawrence

Oct 9, 2008

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3127 views

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25:45

The role of mechanistic models in Bayesian inference

Dan Cornford

Oct 9, 2008

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3609 views