1. CSI 661 - Uncertainty in A.I. Lecture 141 The Bigger Picture (Sic) If you saw this picture, what game would you infer you were watching? How could we get a machine to make such inferences?

2. CSI 661 - Uncertainty in A.I. Lecture 142 Which Algorithm To Use Metropolis sampler –Global vs component Gibbs sampler Dynamical algorithms (next lectures, chapter 5 Neal)

3. CSI 661 - Uncertainty in A.I. Lecture 143 Behavior Over Time Initial State: TFT

4. CSI 661 - Uncertainty in A.I. Lecture 144 Dynamics of Gibbs and Metropolis Samplers What determines convergence? Motivating simple two dimensional case. Dynamics of movement Mixing, poor mixing, Multi-modality, stickiness, sensitivity to initial conditions Invariance to co-ordinate transformations –Translation, scaling, rotation

5. CSI 661 - Uncertainty in A.I. Lecture 145 Methods to Improve Movement Reparameterization Adaptive directional sampling Modifying the stationary distribution Metropolis Coupled MCMC (MCMCMC) Simulated tempering Tempered transitions