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Signals, Waves, and Learning: A Data-Driven Paradigm for Wave-Based Inverse Problems

Project description

Theory combined with experience keep scattering algorithms on track

Imagine a cue ball struck in the first play of a pool game, traveling with significant kinetic energy toward the rest of the balls huddled en masse awaiting their fate. These balls scatter upon impact in ways that can be predicted readily given all the physical parameters of the system such as masses, friction coefficients, and velocity vectors. Scattering of energetic waves in other situations due to imperfections in the medium of transmission can be much more complicated; however, accurate prediction is fundamental to tasks in fields from biomedicine to seismology. The EU-funded SWING project plans to boost the power of scattering computational algorithms by combining theoretical approaches with data-driven (deep learning) ones while defining the limits of each.

Call for proposal

ERC-2019-STG
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Host institution

UNIVERSITAT BASEL
Address
Petersplatz 1
4051 Basel
Switzerland
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 1 986 430

Beneficiaries (1)

UNIVERSITAT BASEL
Switzerland
EU contribution
€ 1 986 430
Address
Petersplatz 1
4051 Basel
Activity type
Higher or Secondary Education Establishments