MLSS 2012: N. Lawrence - Session 1: Motivation and Linear Models (Part 1)
MLSS 2012: N. Lawrence - Session 3: Nonlinear Probabilistic Dimensionality Reduction
MLSS 2012: N. Lawrence - Session 4: Introduction to Learning with Probabilities (Part 1)
MLSS 2012: N. Lawrence - Session 4: Introduction to Learning with Probabilities (Part 2)
MLSS 2012: N. Lawrence - Spectral approaches to dimensionality reduction (Part 1)
MLSS 2012: N. Lawrence - Session 1: Motivation and Linear Models (Part 2)
MLSS 2012: N. Lawrence - Spectral approaches to dimensionality reduction (Part 2)
Introduction to Machine Learning -- Neil Lawrence (Part 1)
MLSS 2012: J. Cunningham - Gaussian Processes for Machine Learning (Part 1)
Neil Lawrence Gaussian Processes Part 2
MLSS 2012: M. Girolami - Diffusions and Geodesic flows in Manifolds... (Part 2)
MLSS 2012: J. Cunningham - Gaussian Processes for Machine Learning (Part 2)
Neil Lawrence - Gaussian Processes Part 1
MLSS 2012: D. Gorur - Session 2: Dirichlet Processes: practical course
MLSS 2012: G. Lugosi - Session 1: Concentration Inequalities in Machine Learning (Part 2)
Gaussian Processes with Neil Lawrence
Gaussian Processes Part I - Neil Lawrence - MLSS 2015 Tübingen
MLSS / AISTATS 2012: Bayesian Modelling
AISTATS/MLSS 2012: Nonparametric Bayesian Modelling / Graphical Models, Part B
MLSS 2012: B. Schölkopf - Session 2: Kernel Methods (Part 2)
