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Deep learning and inverse problems


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27th September 2021 to 1st October 2021
Simon Arridge

Workshop theme:

Classical research on inverse problems has focused on establishing conditions which guarantee that solutions to ill-posed problems exist and on methods for approximating solutions in a stable way in the presence of noise. Despite being very successful, such a knowledge-driven approach is also associated with some shortcomings. First of all, a mathematical model is never complete. Secondly, most applications will have inputs which do not cover the full space but stem from an unknown subset or obey an unknown stochastic distribution.

For these reasons, recent research in inverse problems seeks to develop a mathematically coherent foundation for combining classical model-driven approaches, with data-driven models, and in particular those based on deep learning. As an application area of deep learning, inverse problems, however, occupy a special role as the inherent and unavoidable instability of inverse problems - which cannot be remedied by preconditioning or any other type of data preprocessing - is reflected by the failure of naively transferring deep learning concepts from image processing directly to inverse problems in tomography, non-destructive testing or monitoring physical-technical processes in general.

So far several concepts with stunning experimental results have been published for combining model-based approaches for inverse problems with DNNs, however, no consistent theory exists. We expect that discussions at and collaborations stemming from this workshop will contribute towards the creation of a mathematically sound theory and they have the potential to shape future mathematical research in this field.

Deadline for applications: 27th June 2021

MDL programme participants DO NOT need to apply, programme participants with visit dates during MDLW02 will automatically be added to the attendee list.

Please note members of Cambridge University are welcome to turn up and sign in as a non-registered attendee on the day(s) during the workshop and attend the lecture(s). Please note that we cannot provide you with any support including name badge, meals or accommodation.

In addition to visiting the INI, there are multiple ways in which you can participate remotely.

Apply now


Registration Only    
  • Registration Package: £TBC
  • Student Registration Package: £TBC

The Registration Package includes admission to all seminars, lunches and refreshments on the days that lectures take place (Monday - Friday), wine reception and formal dinner, but does not include other meals or accommodation.

Formal Dinner Only
  • Formal Dinner: £50

Participants on the Accommodation Package or Registration Package, including organisers and speakers, are automatically included in this event. For all remaining participants who would like to attend, such as programme participants, the above charge will apply.


Unfortunately we do not have any accommodation to offer so all successful applicants will need to source their own accommodation.  Please see the Hotels Combined website for a list of local hotels and guesthouses.



Lunch timings and location will be confirmed with timetable.

Evening Meal

Participants are free to make their own arrangements for dinner.

Formal Dinner

The Formal Dinner location and date is to be confirmed. Participants on the Accommodation Package or Registration Package, including organisers and speakers, are automatically included in this event.

University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons