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Isaac Newton Institute for Mathematical Sciences

Neural Networks and Machine Learning

July - December 1997

Organisers: C M Bishop (Aston), D Haussler (UCSC), G E Hinton (Toronto), M Niranjan (Cambridge), L G Valiant (Harvard)

A Newton Institute EC Summer School

PROBABILISTIC GRAPHICAL MODELS

1 - 5 September 1997

Organisers: C M Bishop (Aston) and J Whittaker (Lancaster)

View graphs of seminars

Click on the preferred file type to download the viewgraphs from the seminars. (Please note that some have two sets).

Christopher Bishop (Aston) Latent variables

Phil Dawid (London) Conditional Independence for Statistics and AI

Ed George (Texas) Empirical Bayes Covariance Selection

Wally Gilks (Cambridge) Simulation Methodology for Dynamic Models

David Heckerman (Microsoft) Directed Acyclic Graphs: Representation and Learning

Tommi Jaakkola (MIT) Bayesian Estimation in the Presence of Missing Values

Mike Jordan (MIT) Approximate inference via variational techniques

Stuart Russell (Berkeley) Learning: temporal processes and structure

Ross Shachter (Stanford) Causal Models: What does one need to know?

Prakash Shenoy (Kansas) Some Improvements to the Shenoy-Shafer Architecture for Computing Marginals

David Spiegelhalter (MRC, Cambridge) Bayesian Graphical Modelling

Milan Studeny (Praha) On separation criterion for chain graphs

Joe Whittaker (Lancaster) Graphical models

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