Start Discovering Solved Questions and Your Course Assignments
TextBooks Included
Active Tutors
Asked Questions
Answered Questions
how difficult is it to get dna into a narrow tubeto an information theorist the entropy associated with a constrained
a classic example of a constrained channel with variable symbol durations is the lsquomorse channel whose symbols
pick a variable that is supposedly bell-shaped in probability distribution gather data and make a plot of the variables
imagine that we reparameterize a positive variable x in terms of its cube root u x 13 if the probability density of x
find the most probable code word in the case where the normalized likelihood is 02 02 09 02 02 02 02 also find or
1 what is the constant of proportionality2 confirm that the above sum-product algorithm does compute ptn t
consider a one-dimensional random walk on each step of which the state moves randomly to the left or to the right with
show that this individual transition leaves invariant the conditional distribution xi sim normal micro sigma2a single
markov chain monte carlo methods do not compute partition functions z yet they allow ratios of quantities like z to be
the transition matrix tx x defined by a complete update of all variables in some fixed order does not satisfy detailed
discuss how the effectiveness of skillings method scales with dimensionality using a correlated n-dimensional gaussian
implement gibbs sampling for the inference of a single one-dimensional gaussian which we studied using maximum
prove that detailed balance implies invariance of the distribution px under the markov chain tproving that detailed
what would be the best way to extract the entropy from the monte carlo simulations what would be the best way to obtain
is there any relationship between the probability distribution of the time taken for all trajectories to coalesce and
1 investigate the application of perfect sampling to linear regression in holmes and mallick 1998 or holmes and denison
how can you use a coin to create a random ranking of 3 people construct a solution that uses exact sampling for example
finding the partition function z of a probability distribution is a difficult problem many markov chain monte carlo
1 what do you think of the idea of using a variational method to optimize an approximating distribution q which we then
find the bayesian inference about the bias pa of the coin given the data and determine whether a bayesians inferences
two ordinary dice are thrown repeatedly the outcome of each throw is the sum of the two numbers joe shark who says that
the preceding exercise parts b and c involved a utility function based on regret if one married the tenth most
one of the challenges of decision theory is figuring out exactly what the utility function is the utility of money for
the four doors problema new game show uses rules similar to those of the three doors but there are four doors and the
in the bayesian graphical model community the task of inferring which way the arrows point - that is which nodes are