David MacKay
homepage:http://www.inference.phy.cam.ac.uk/mackay/
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Lectures:

lecture
flag Lecture 16: Data Modelling With Neural Networks (II): Content-Addressable Memories And State-Of-The-Art Error-Correcting Codes
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
1135 views
  lecture
flag Lecture 15: Data Modelling With Neural Networks (I): Feedforward Networks: The Capacity Of A Single Neuron, Learning As Inference
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
1855 views
lecture
flag Lecture 14: Approximating Probability Distributions (IV): Variational Methods
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
1500 views
  lecture
flag Lecture 13: Approximating Probability Distributions (III): Monte Carlo Methods (II): Slice Sampling, Hybrid Monte Carlo, Over-relaxation, Exact Sampling
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
1448 views
lecture
flag Lecture 12: Approximating Probability Distributions (II): Monte Carlo Methods (I): Importance Sampling, Rejection Sampling, Gibbs Sampling, Metropolis Method
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
2314 views
  lecture
flag Lecture 11: Approximating Probability Distributions (I): Clustering As An Example Inference Problem
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
1376 views
lecture
flag Lecture 10: An Introduction To Bayesian Inference (II): Inference Of Parameters And Models
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
2376 views
  lecture
flag Lecture 9: A Noisy Channel Coding Gem, And An Introduction To Bayesian Inference (I)
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
1622 views
lecture
flag Lecture 8: Noisy Channel Coding (III): The Noisy-Channel Coding Theorem
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
1318 views
  lecture
flag Lecture 7: Noisy Channel Coding (II): The Capacity of a Noisy Channel
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
1381 views
lecture
flag Lecture 6: Noisy Channel Coding (I): Inference and Information Measures for Noisy Channels
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
1711 views
  lecture
flag Lecture 5: Entropy and Data Compression (IV): Shannon's Source Coding Theorem, Symbol Codes and Arithmetic Coding
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
1838 views
lecture
flag Lecture 4: Entropy and Data Compression (III): Shannon's Source Coding Theorem, Symbol Codes
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
2337 views
  lecture
flag Lecture 3: Entropy and Data Compression (II): Shannon's Source Coding Theorem and the Bent Coin Lottery
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
2515 views
lecture
flag Lecture 2: Entropy and Data Compression (I): Introduction to Compression, Information Theory and Entropy
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
4891 views
  event
flag Course on Information Theory, Pattern Recognition, and Neural Networks
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
together with: David MacKay (University of Cambridge) (produced by),
lecture
flag Lecture 1: Introduction to Information Theory
as author at  Course on Information Theory, Pattern Recognition, and Neural Networks,
20967 views
  tutorial
flag Information Theory
as author at  Machine Learning Summer School (MLSS), Cambridge 2009,
14560 views
lecture
flag Gaussian Process Basics
as author at  Gaussian Processes in Practice Workshop, Bletchley Park 2006,
41599 views