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.

Fields of science

• engineering and technology › electrical engineering, electronic engineering, information engineering › electronic engineering › signal processing
• natural sciences › computer and information sciences › artificial intelligence › machine learning › deep learning

Programme(s)

• H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)

Topic(s)

• ERC-2019-STG - ERC Starting Grant

Call for proposal

ERC-2019-STG
See other projects for this call

Funding Scheme

ERC-STG - Starting Grant

Leaflet | Map data © OpenStreetMap contributors, Credit: EC-GISCO, © EuroGeographics for the administrative boundaries

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