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which for the introduction i'm welcome everybody to the second session so
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um can machine earning help you discover what you don't know
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um so let me first give an overview of the group so the uncertainty qualification and optimal design group was
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created in step that on september two thousand fifteen and so this is soon the third anniversary and um
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we are currently you a very small group there is one permanent one intern and one visit
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to master students but they already a six a and nine uh including visiting students
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and uh as i haven't mentioned awesome special economic ties to a university of them
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and in particular the institute of not directed at medical statistics and uh actuarial sciences
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since the last uh advisory board um there's been one projects that was
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completed in the group which is learning and is very easy
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usually saying a dangerous regions in most right part arm into space which was funded by the uh has information
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i would comment on the outcomes of this project in a in a few slides
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and uh now we have a new project that is starting um was two
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pages students that are hired uh in the frame of the project
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uncertainty qualification and efficient design of experiments for data and simulation for even
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inverse problem solving that is funded by this with national science foundation
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so um it's about small data indeed and um
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the group focuses on production optimisation and inversion
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uh in the framework of complex systems that are typically quite expensive to sample up to evaluate
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and the core methodological approaches of the group uh rely on a gaussian process modelling
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a basin optimisation base inset estimation and and sequential
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design algorithms named sequential uncertainty reduction artworks
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so the main application domains and partners include the
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environmental joe sciences with uh several collaborations with
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union was an initial then uh the french geological survey b. r. d. or g. m.
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accept rock uh energy engineering with the french nuclear safety institute's also with
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the kind of your those salt dodge energetic and see that nothing
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and also uh inclined dynamics was the uh national centre for climate change research and um
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also this is a group that has a reparations with other groups so uh we started the uh some
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preparations in a robotic spectacle busted bar and the watching by metrics uh what's the best around them
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so uh the kind of uh the flagship example that some of you might already
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know of of the group is uh um uh for all the problem
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so here we are looking at a a simulation of how a contaminant
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care and propagate in a subset it's so it's a two d.
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section of a of a phonetically fair so a a natural uh has a lot of water
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and we are uh assuming that at time zero there
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is the contaminants that is starting its uh
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flow in the subset face and here we are monitoring at different wells
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so you can see the triangles though this pen for wells
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was the colours that are paired with the this uh the two
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figures where we're observing the concentration of contaminants all the time
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so at every well you have this uh the the flow is
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taking place we measure the consultation contaminants and then the game
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is uh to try to recover the starting position of the contaminants from discussed
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which seems like a mission impossible because you have the the information you have
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is is relatively little compared to the complexity of ah of the phenomenon
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but we are trying to use a base in experimental design and basin of
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summarisation algorithms to to to recover this so here this is complete
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a synthetic best case where everything's controlled so we know whether component was started
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because uh it was imposed the simulation and we are relying on the on the steps of salvation you're you're trying to recover this
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so we'll come back to the sinner insect but before that a bit well that's that that's uh let me come back
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a notion of uncertainty quantification so uh you might that's not well uh be uh
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informed yet about what you q. means ostensible so it's a relatively recent dissipate
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it's a discipline that is intrinsically uh at the interface between
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several disciplines which or name the scientific computing and statistics
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and the goal of you q. is to predict complex systems um
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like a pink numerical simulations and and data driven statistical procedures
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so um this field as has really been from rushing
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in recent years in particular are there is a
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total that was announced into doesn't thirteen by uh that's i am and a essay that all that
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a society of industrial not by mathematics and the uh american statistical association
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uh and uh and also the there was recently a six month program
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at the isaac newton's you didn't enrich about you q. for
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complex systems period of the budget so this is just to show
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you a two two examples of this uh drawing uh
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field and ah optimal design in the name of the group stands
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primarily for model based design of experiments so in particular experiments at the very expensive
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uh to perform a with an emphasis on sequential design of numerical simulations
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design of experiments is a diary of statistics and design of numerical simulation is an area that
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is developing um because more and more we replace
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a year field experiments by artificial experience
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so if we come back to our uh for all problem here you have an example
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of how this base unit to my session and reasons the work correctly so
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here we are looking at the objective function the objective function you if you
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remember that that's case you had these three different carols that you wanted
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a base on in order to involve the system and find the contaminant
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location so basically if you take any comedic location for the contaminants
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source you can run the full simulation also the candles and calculated the misfits between the
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reference cows and the hypothetical uh curves obtained
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by moving the contaminate contamination source
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and then if you look at this picture yeah what you see is how this
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integrated at all is behaving when you move the hypothetical location of the contaminants
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and what you see is that there is a unique point of minimum
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your green and this point is actually the real actual oh
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place where the contaminants uh start it's and what you want is to find
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this place which is basically a global optimisation problem you want to find
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the global minimum of this very complicated normally they are horrible curve or not
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uh based on a few experts you start by doing so naive experiments the blue
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points of schools based in in design and then you can approximate this misfits
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based on the nine a blue points and you ups you get a a very very naive representation
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of this complicated function based on mine what's your but that also comes with some uh
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creation of production and so tainted and by combining these two maths you can
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guy either a sequential design main meaning that you can add
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new simulations in order to hopefully converge with this
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a green ones so here uh we are using the so called expect improvement your
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stick strategy to our uh uh points which is uh the right point
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and meaning that we we're going to really perform the simulation at this point and
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then we are going to calculate the misfits and we will see that this orange new points here
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is affecting the model is affecting the answer change c. n. is meeting asked when you are yeah and then
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we're going to iterate this and by iterating that we're
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going to explore this complicated mourning out on stage
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and eventually after about twenty rounds we're going to explore and to find the global optimum
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get so instead of running full grades of calculation over the two dimensions here we can
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uh rely on a relatively moderate budget and find the source of contamination of
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course this is a two example once a small dimension there's a lot of work
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going on to expand this uh to higher dimensional problems and many other changes
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so this is a test case that you might have already have uh come across in particular uh if you remember for
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the yeah people the son of g. p.'s that'd yep last year that we uh animated without your the monty
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there is also prevent available on this test case and this is a joint work with people project can with
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the the job i don't i'm using this boldface uh to uh the notes uh the the um alumni
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now she's in a she's a permanent a lecture at the medical university in the bangkok thailand
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young people is a little thawing as opposed docket inverse of the japanese also collaboration misshapen now uh the shot that
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but that wasn't so i'm just of couple of words about recent extensions of this so we
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have a uh just try to to to do batch sequential design on this and show
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would the obtain some nice results uh showing the the benefits of but analysing the expiration
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on this this case uh with this whole teen and adult amount as well and
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we are currently considering an extension of that to uh the case where the digit lodges and something as well
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so now let me um speak briefly about some recent achievements
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first about the as a project on a learning in the visualising dinners regions
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and then um the very short overview of some other recent contributions in finite finally
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i if time allows i uh speak briefly about some projects ongoing out it's
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so this has the project has enabled the support of that yachtsman see as a post op
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ah let me just mention that shall have been before long term visit thoughts you uh and the group while a
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performing is is p. h. d. studies that you don't do it now as opposed look at it yeah
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and this is a project that has a involved a a more a test
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case with the french geological survey that that we'll speak about right now
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so they'll simulating a frauds and assimilating
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basically a coastal flooding risks um
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yeah the atlantic shore in uh in france yeah that was set and uh they're particularly focusing here
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on the small regions around the site people showed up and the they are looking at
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um the um the prodding expand its depending on
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the wave and other physical uh parameters
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so the operator rising the simulation using five inputs um that all the
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forcing parameters that or formant rising that fight fight and search and
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the or more the link the uh the fraud in impact over the
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in aunt ah and in particular the total are we offering
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as a function of this five arm is what they want to know is what is the regions
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of the five dimensional space uh that all leading to a floating above a given fresh
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so uh we is that it would not go to get the l. g. m. with developed the method based on uh
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courtenay profile max of um a profile maxima quite tonight of annexing off a
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that is a a method to visualise an expression sets in high dimensions
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based on the maximum of or the remaining viable so for
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each viable weekend brought how the supreme i'm off
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the the complex system is behaving when this dimension is is change
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it is a very complicated function because this is a supreme uh so it's uh
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it's really it's missus states a lot of uh evaluations and since we cannot
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perform a lot of evaluation we use gaussian process is but if you take the supreme of goes imposes is you get something that is not gets in
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so did it lead us to some um relatively hardcore developments and we could come up
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with some quantification of uncertainties on the production of the supreme of goes imposes is
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uh which uh enable us to put you discover sent to know what's or
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the ranges of parameters that never lead always lead to some excursions
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so this is a developed in the paper uh that is to to be resubmitted your
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um with the belgian collect colleagues and we have also within this project
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this more as a project we have also uh revise the
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paper about often probability estimation that is not published in a just
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a g. s. and uh we have also uh oh
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based on this we also concede the currently i'm
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revising this work on conservative said destination which
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is presented in more detail in the pasta but you can see and the whole
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so these are some of the recent papers don't have time to go into detail
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about that but just to show you will working on in finances and crawls
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oh also was high dimensional methods withdrawals ah and the
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uh mixtures between yeltsin process moldings and wait let's
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also doing some um work collaborative work on your shoe
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for hydrogen hydrogen physics where we're basically transferring recent advances and not
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to uh apply communities and also um the formations and be
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riveted basic control design for functions be settled and citations
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there is also another point o. of importance is the
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climate than energy related contributions so very gleefully
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we have hosted um the internship and on and on net in collaboration with the with
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the centre for climate change research and we have worked on nonstationary time series
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of extreme values with application kind advances is is not published yet but something ongoing
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and the uh we have also a longstanding collaboration with
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people working notably on the modelling of hail
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um that's the pain is a is a is an important risk for the economy
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and the um um we have used a possum regression model uh to uh
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to the chance of a whole day's involved in switzerland that was but which
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wasn't enough was very research and finally at the nice good to
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is now doing an internship on a new collaboration with the the clan where
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we are using global sensitivity analysis to analyse impact of market parameters
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uh on the to the optimal energy boards so we have a function
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that is a yeah a that is the result of us over
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we are analysing how ah changes in parameters affect the uh best
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response of this over all the uh optimum values of inputs
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okay ah so finally just some perspectives i'm too much of eighteen problems uh
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for that or um underlined yes and of project that will start soon
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so one of them is coming from computational cosmetology so here we are working always computational
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'cause manages from a th so this is the plan and uh they have some
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telescope images of the universe and offering to bet on this the new house and you need a cell some constants was medical
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constants that are uh that are not known precisely but once you
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assume values for this possible illegal constants you can simulate
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how this telescope image ah could look like
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well from a physical gravitational models
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so basically the same day the whole universal portion of the universe and they come up with is
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the distribution of active galaxies and what they want is to find those magical parameters that much
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who is the um the statistical properties of galaxies that they actually up so
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and for that they need methods that of sequential and that uh will choose which simulation to run
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uh in order to best identified a spot on those and we will uh develop some novel approaches that
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another problem we all uh i'm facing is uh the design
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of experiments on actual uh a complex systems from nature
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namely volcanoes so here this is a collaboration with a unicef roseanne and the group of that's in there
00:17:34
and the the idea is that we use a basin inversion so
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here to based on reading actually measurements we want to find
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um the density inside of a volcano and most specifically to identify regions of past activities which correspond
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to high density or too high grade intensity of the high coverage of them to to
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and uh what we want to do is to design the experiments actually pretty
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much measurements on the volcano an optimal weight on the some basic model
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so as a final word subgroup that is developing ah it's developing research
00:18:07
group is a solid methodological backgrounds and the number of research perspectives
00:18:12
and we are very open to discussions with potential partners and it's like

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Conference Program

Introduction by Hervé Bourlard
BOURLARD, Hervé, Idiap Director, EPFL Full Professor
Aug. 29, 2018 · 9:03 a.m.
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Presentation of the «Speech & Audio Processing» research group
MAGIMAI DOSS, Mathew, Idiap Senior Researcher
Aug. 29, 2018 · 9:22 a.m.
16949 views
Presentation of the «Robot Learning & Interaction» research group
CALINON, Sylvain, Idiap Senior Researcher
Aug. 29, 2018 · 9:43 a.m.
9721 views
Presentation of the «Machine Learning» research group
FLEURET, François, Idiap Senior Researcher, EPFL Maître d'enseignement et de recherche
Aug. 29, 2018 · 10:04 a.m.
14111 views
Presentation of the «Uncertainty Quantification and Optimal Design» research group
GINSBOURGER, David, Idiap Senior Researcher, Bern Titular Professor
Aug. 29, 2018 · 11:05 a.m.
3210 views
Presentation of the «Perception and Activity Understanding» research group
ODOBEZ, Jean-Marc, Idiap Senior Researcher, EPFL Maître d'enseignement et de recherche
Aug. 29, 2018 · 11:24 a.m.
5620 views
Presentation of the «Computational Bioimaging» research group
LIEBLING, Michael, Idiap Senior Researcher, UC Santa Barbara Adjunct Professor
Aug. 29, 2018 · 11:45 a.m.
4130 views
Presentation of the «Natural Language Understanding» research group
HENDERSON, James, Idiap Senior Researcher
Aug. 29, 2018 · 2:03 p.m.
8976 views
Presentation of the «Biometrics Security and Privacy» research group
MARCEL, Sébastien, Idiap Senior Researcher
Aug. 29, 2018 · 2:19 p.m.
6512 views
Presentation of the «Biosignal Processing» research group
RABELLO DOS ANJOS, André, Idiap Researcher
Aug. 29, 2018 · 2:43 p.m.
4027 views
Presentation of the «Social Computing» research group
GATICA-PEREZ, Daniel, Idiap Senior Researcher, EPFL Adjunct Professor
Aug. 29, 2018 · 2:59 p.m.
7158 views

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