So, welcome everyone.

So today we have Professor Wolfgang Damme from the University of South Carolina who

will be speaking about state definition, the role of reuse models.

Please Professor Damme, you have the floor.

Okay, yeah, welcome everybody.

It's a pleasure to use this virtual medium to meet you.

I should say this is joint,

well, these are excerpts of joint work with various people.

Among them, long standing collaborators

like Albert Cohen, Ron DeVore, Olga Moula, James Nichols.

He is currently in Australia.

And then when I have time,

the last part of the lecture will be ongoing joint work

with these two people,

which is Min Wang from Duke and Zhu Wang

from my department in South Carolina.

Okay, so why can't I advance now?

Ah, I can.

So here is a brief outline.

I will first try to capture what this is all about.

And it has its various subjects there.

It has to do with models and data

and how to be able to extract best information

from both sources.

I will present a geometric perspective,

which is maybe uncommon

and not so much in line with the traditional approaches.

And there is one more cause,

which we call the one space method.

And in addition, I will try to bring out

what the benchmarks are.

The whole talk is about estimation problems,

so inverse problems.

And from the very beginning,

we first posed the question, what can you get at best?

And then these benchmarks sort of guide

the algorithmic development,

namely try to come up with schemes

that actually meet in the end those benchmarks.

And the question is whether this is actually possible.

And we'll see that with a common scheme,

this is not possible,

but a certain nonlinear estimator,

which is based on this one.

By the way, do you see my cursor?

Yes, do you?

Yes.

Okay, so we'll achieve it.

And if there is time left,

I will address something that's probably burning