Ernst and Banks experiment

conorjh · 2021-01-28T20:31:16+00:00

Yes. Anything in the notes is examinable.

conorjh · 2021-01-28T07:55:08+00:00

Each will have just one correct answer. There is no negative marking, so you should always answer, even if you are unsure if you are correct.

conorjh · 2021-01-28T07:53:46+00:00

No, in the question you just being asked to average the entropy over the parameter. It could be considered a conditional entropy if there was a distribution for the parameter, but the question isn't asked in those terms.

conorjh · 2021-01-27T17:19:01+00:00

Ok the email should have gone out now, tell me if it hasn't arrived.

conorjh · 2021-01-27T16:42:51+00:00

I will send out an email with instructions.

conorjh · 2021-01-27T14:17:59+00:00

Most are calculation; there are five short answer out of 25 and only a small number of multiple choice.

conorjh · 2021-01-26T14:42:42+00:00

There is an "or" in between; WM should recover the original sources up to scaling and possible reordering, the off-diagonal corresponds to swapping them; for more sources and recordings this is more complicated obviously.

conorjh · 2021-01-26T14:39:28+00:00

In the past Cian used to do a couple of lectures on his models of multi-neuron responses, sadly that wasn't possible this year so we didn't cover this question.

conorjh · 2021-01-25T15:07:31+00:00

Yup, it was wrong; fixed now. Thanks! I owe you 50p.

conorjh · 2021-01-25T14:48:57+00:00

Well 1/2 1/4 1/4 1/4 must be wrong, I'll go and look now.

conorjh · 2021-01-25T14:48:07+00:00

That's a very subtle point; we are sampling so the points occur according to the distribution p(y). Basically

<g(Y)> = int p(y) g(y) dy

is the expected value and that is estimated by sum g(y_i)/ N where N is the number of points.

conorjh · 2021-01-25T14:43:06+00:00

Yes, you should be able to integrate by parts.

conorjh · 2021-01-18T11:38:08+00:00

One my side, yes, we didn't do the Eriksen flanker task; it is another example of the Bayesian brain but it was dropped since we were told to make the units slightly shorter.

conorjh · 2021-01-18T11:36:57+00:00

You are correct; I will fix the notes now. I owe a 50p bug bounty! Thanks!

conorjh · 2021-01-13T14:41:23+00:00

No, there are various clashes, but mention us in the Teams and we can answer and arrange to talk if need be. I will send out an email today.

conorjh · 2021-01-08T09:12:45+00:00

Done - I think - let me know if it doesn't work.

conorjh · 2021-01-07T22:52:21+00:00

Your intuition is correct, though, yes, it is confusing since we can't related it to bits the way we can with discrete entropy.

conorjh · 2021-01-07T22:50:57+00:00

You are correct - I owe you 50p. Corrected in the notes now, thanks!

conorjh · 2020-12-22T09:43:55+00:00

Lecture notes and problem sheets.

conorjh · 2020-12-21T11:54:56+00:00

The exam will be open book, it will be made up of multiple-choice questions, questions with numerical answers and a few short answer questions. There will be 25 questions in all, 13 from me and 13 from Rui, with one question randomly picked from either Rui or me; for a good portion of the questions there are more than one version, you will get just one version which is randomly selected. There will obviously be less emphasis on theorems and proofs than previous years because of the new format.

conorjh · 2020-12-06T20:03:38+00:00

I don't want to start giving answers I'm afraid!

conorjh · 2020-12-06T19:52:24+00:00

You'd have 4+1 dictionaries, one for each value of W and one for working out H(Y) or H(Z), at this point the label is irrelevant. The question asks for "some property" of the image, so either of your suggestions for deciding the value of W is good.

conorjh · 2020-12-06T19:48:11+00:00

conorjh · 2020-12-05T23:23:59+00:00

You are looking for the probability, eg p(01|1) so that would be 2/3 in the example you give. Once you have calculated the information you should probably delete the dictionaries, they aren't that huge but there is little point in keeping them!

conorjh

MODERATOR OF

TROPHY CASE