David MacKay

Name:	David MacKay
Affiliation:	Cavendish Laboratory
E-mail:	(only provided to users who are logged into talks.cam)
Last login:	Tue Mar 01 10:22:30 +0000 2016

Public lists managed by David MacKay

Talks given by David MacKay

Obviously this only lists talks that are listed through talks.cam. Furthermore, this facility only works if the speaker's e-mail was specified in a talk. Most talks have not done this.

• Flying fish
• Data Modelling With Neural Networks (II): Content-Addressable Memories And State-Of-The-Art Error-Correcting Codes
• Approximating Probability Distributions (IV): Variational Methods
• Advanced Monte Carlo Methods and Variational Inference
• Clustering, Laplace's Method, Monte Carlo Methods (I)
• Clustering, Laplace's Method, Monte Carlo Methods (I)
• Approximating Probability Distributions (I)-(II): Monte Carlo Methods and Variational Inference
• An Introduction to Statistical Inference, Data Modelling & Pattern Recogntion
• Communication over noisy channels (III)
• Communication over noisy channels (II)
• Communication over noisy channels (I)
• Entropy and data compression (IV)
• Entropy and data compression (III)
• Entropy and data compression (II)
• Entropy and data compression (I)
• Introduction to information theory
• Sustainable energy without the hot air
• Sustainable energy plans that add up
• Sustainable Energy - without hot air
• Energy plans that add up
• Sustainable Energy – Without the Hot Air
• Sustainable Energy - without the hot air
• Education of Climate Change at Cambridge & Beyond
• Sustainable Energy Without the Hot Air
• Sustainable Energy - without the hot air
• Tutorial on Monte Carlo methods
• Physical Limitations on Energy Supply
• Error Correcting Codes
• Numbers, not adjectives - a rough guide to the sustainable energy problem
• Bliss-Dasher -- Efficient semantic writing with any muscle
• Sustainable Energy - Without the BS (Director's Cut)
• Kingman's coalescent, non-parametric Bayesian agglomerative clustering
• Sustainable Energy - Without the BS
• Sustainable Energy - Without the Hot Air
• Estimation of non-normalized statistical models using score matching
• Sustainable Energy - Without the Bullshit
• An interesting preprint

Talks organised by David MacKay

This list is based on what was entered into the 'organiser' field in a talk. It may not mean that David MacKay actually organised the talk, they may have been responsible only for entering the talk into the talks.cam system.

• Introduction to IFM's Distributed Information and Automation Laboratory
• Advanced automated assembly and repair round-table
• Hydrogen fuel cells
• Combining Collaborative Filtering with Meta Data for Scalable Recommendations
• A quick way to learn a mixture of exponentially many linear models
• Inferring building properties from temperature data
• Literature review presentations - Tidal power, and Fuel cells
• Deducing Principles in Natural Perception
• Geothermal power in Australia
• Cloud Ships for global warming reduction
• Dasher in Mandarin Chinese with Phonetic Pin Yin
• Optimizing Similarity Functions in Various Pattern Recognition Problems
• Visual Search: Applications and Computational Modelling
• Eye-Tracking in Virtual Reality
• Estimating the Pen Trajectories of Handwritten Static Scripts using Hidden Markov Models
• Power to Choose: How the energy choices people make will change their lives.
• Bayesian Inductive Programming
• Thermochemistry and Nuclear power - Clean responsive electricity
• Low-cost large-scale renewable energy
• Inferring the hazard rate in change point models
• Clustering by linear programming, convex optimization and belief propagation
• Artificial intelligence in combinatorial game design
• From Automated Currency Validation to Protein Fold Recognition: Probabilistic Multi-class Multi-kernel Learning
• Semantic Texton Forests for Image Categorization and Segmentation.
• Bayesian Models for Dependency Parsing Using Pitman-Yor Priors
• Gaussian Process Density Sampler
• Some models for biology
• (clashing event: Sustainable Energy and Arithmetic)
• Image superresolution
• Infera - a Bayesian team-ranking program from 1996
• Non-Rigid Photometric Stereo with Colored Lights
• NIPS presentations
• Composing: Linear and Non-Linear Thinking
• Life beyond the Physics department
• Branch and Bound reconstruction of Balanced Minimum Evolution optimal trees
• The last thing that we should talk about
• Bliss-Dasher -- Efficient semantic writing with any muscle
• Optimal Spreading Sequences for Chaos-Based Communication Systems; Using CSK as a Case Study
• Developing a general-purpose message-passing library
• Short talks about statistical machine learning IIII
• Discussion + tea
• Short talks about statistical machine learning III
• Inference in Gaussian Process models
• Short talks about statistical machine learning II
• coffee
• Short talks about statistical machine learning
• Sequencing hundreds of humans - how to collect the data efficiently and make sense of it
• Coffee + mingle
• Shape writing: a fast and fluid writing system designed for mobile devices
• Five energy plans for Britain
• Minimal Perfect Hashing: hash tables with no collisions
• cancelled
• Shape writing: fluid text entry on mobile devices
• Learning Patterns in the Game of Go
• Inductive Logic Programming and Kernel methods
• Metropolis-Coupled MCMC for Nested Sampling
• Some interesting data: Cryptic DNA sequence periodicities are ubiquitous, organism specific and distinguish introns from exons.
• Title to be confirmed
• Title to be confirmed
• NIPS presentations
• Modeling Natural Sounds with Gaussian Modulation Cascade Processes
• Estimation of non-normalized statistical models using score matching
• HMMs for controlling dynamical systems
• Discussion
• Nuclear fission and fusion
• Tide, Wave, and Offshore Wind
• Biofuels
• Carbon Sequestration
• The Transition from Fossil Fuels
• The Big Picture
• Dynamic imaging of blood flow in the conjunctival and episcleral microcirculations of the human eye: a new chapter in diagnostic imaging?
• Teaching Statistics - A Bag of Tricks
• Leaf Selection for Maximising Diversity in a Tree
• An interesting preprint
• neural phase codes
• Graphical Combinator Programming
• Implicit learning in Music
• Information-Theoretic Security in Wireless Networks: From Theory to Practice
• Music Access for the Disabled
• In search of the brain's wiring
• A Bayesian Unfolding Method Applied to the PAMELA Experiment
• Blissymbolics
• Finite element modelling of growing microtubules
• Capacity of phase-based attractor networks with pairwise couplings
• Joint LDPC Decoding and Timing Recovery Using Code Constraint Feedback
• How to Parameterize a Positive-definite Matrix
• Climate Change: The case for burying CO2
• The Capacity of the Deletion Channel
• Sleeping Beauty and the Armchair Cosmologist
• The 'Rich Club' phenomenon in large networks
• Bayesian approximation for physical inverse problems
• Machine Learning Journal Club: "Gaussian Processes for Machine Learning"
• Machine Learning Journal Club: "Gaussian Processes for Machine Learning"
• Machine Learning Journal Club: "Gaussian Processes for Machine Learning"
• The Puppet Master - How the brain controls the body.
• SURVIVAL INTO THE FUTURE
• SURVIVING LONGER
• Protein Folding. Misfolding and disease.
• SURVIVING POVERTY AND FAMINE
• Machine Learning Journal Club: "Dependent Gaussian Processes"
• Machine Learning Journal Club: "Assessing Approximations for Gaussian Process Classification"
• Inositol: evolution's favourite molecule?
• Machine Learning Journal Club: "Sparse Gaussian Processes using Pseudo-inputs"
• SURVIVAL OF LANGUAGES
• reading-group: Divergence measures and message passing
• SURVIVAL OF CULTURE
• reading-group: Expectation Propagation
• reading-group: Interpolating Between Types and Tokens by Estimating Power-Law Generators
• Evolution of the Earth
• reading-group: TD-Gammon
• Packaging the genome: chromatin, DNA architecture and the role of proteins
• Reading Group: "Learning to Predict by the Methods of Temporal Differences"
• The Free Will Theorem
• Our Dynamic Sun
• multicanonical sampling
• Reading group: Bayesian inference via search