With likelihood weighting, we fix the evidence variables.

And this weighting is relatively straightforward to apply in Gaussian fitting.

So, if we measured zero point zero zero seven zero zero kilometers.

So what's zero, plus zero, plus zero, plus zero?

Likelihood weighting is a great technique, but it doesn't solve all our problems.

Zero plus zero plus zero ten times is still zero.

1, zero, minus 1, zero, 1, zero.

So 1, zero, minus 1, zero, positive, zero, negative, zero, positive.

One, one, point zero zero one, zero zero one, dot dot dot.

Sine of zero is zero, so minus zero is still zero, so this is zero. f prime prime of zero.

How many 5s have I seen? Zero, zero, zero, zero, 1, 2, great.

And because of this left weighting, the average is actually here, way to the left.

So, times zero, times zero.

Anything times zero is zero.

Zero times 3 is zero.

Sine of zero is zero.

Zero

Zero

Zero.

Zero.

So four plus zero plus zero.

And you get six zero zero.

Zero times twenty five is zero.

So, anything times zero is zero!

Eight point two five minus zero point zero one zero five.

So you don't have to memorize your zero multiplication tables because everything times zero is zero, or zero times anything is zero.

You know, let's say, usually you initialize your parameters at zero for zero, theta zero and zero.

Sign of zero is zero, two times zero is zero, so this whole thing is zero. 1 minus 0 is 1. Fair enough.

So zero to any non zero number, you are going to get zero.

So it's eight point two five and zero point zero one zero five.

Zero Cornered

Zero values

Six zero.

Seven zero.

It's zero.

Well zero.

Zero Six?

And twenty five goes into zero zero times.

The absolute value of zero is just zero.

And then the next routine just implements the simple addition with the measurement_noise as the inverse weighting factor.

For zero to the zeroth being zero and zero to the zeroth power being one.

Squared to zero squared to zero squared which is of course, just equal to zero.

So zero divided by anything that's non zero is just going to equal to zero.

It's about zero sum and non zero sum games.

And the answer is zero, nothing else but zero.