TU1.RA.3

Quantum-assisted machine learning by means of adiabatic quantum computing

Leonardo Tomazeli Duarte, Universidade Estadual de Campinas (UNICAMP), Brazil; Yannick Deville, Université de Toulouse, France
Session:
TU1.RA: Quantum approaches in remote sensing Oral
Track:
Invited Sessions
Location:
Amphitheatre
Presentation Time:
Tue, 16 Apr, 10:00 - 10:15 Algeria Time (UTC +1)
Tue, 16 Apr, 18:00 - 18:15 Japan Time (UTC +9)
Tue, 16 Apr, 09:00 - 09:15 UTC
Tue, 16 Apr, 05:00 - 05:15 New York Time (UTC -5)
Session Chair:
Yannick Deville, Université de Toulouse
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Session TU1.RA
TU1.RA.1: A TAXONOMY OF RELATIONSHIPS BETWEEN INFORMATION PROCESSING, MACHINE LEARNING AND QUANTUM PHYSICS: QUANTUM-INSPIRED, QUANTUM-ASSISTED, QUANTUM-TARGETED AND RELATED APPROACHES
Yannick Deville, Université de Toulouse, France; Leonardo Tomazeli Duarte, Universidade Estaudal de Campinas, Brazil; Alain Deville, Aix-Marseille Université, France
TU1.RA.2: A HYBRID QUANTUM-CLASSICAL CNN ARCHITECTURE FOR SEMANTIC SEGMENTATION OF RADAR SOUNDER DATA
Raktim Ghosh, Fondazione Bruno Kessler, Italy and University of Trento, Italy, Italy; Amer Delilbasic, Gabriele Cavallaro, Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich, Germany and University of Iceland, Iceland, Germany; Francesca Bovolo, Fondazione Bruno Kessler, Italy, Italy
TU1.RA.3: Quantum-assisted machine learning by means of adiabatic quantum computing
Leonardo Tomazeli Duarte, Universidade Estadual de Campinas (UNICAMP), Brazil; Yannick Deville, Université de Toulouse, France
TU1.RA.4: QUANTUM ANNEALING FOR SEMANTIC SEGMENTATION IN REMOTE SENSING: POTENTIAL AND LIMITATIONS
Amer Delilbasic, Forschungszentrum Jülich GmbH, Germany; Bertrand Le Saux, European Space Agency, Italy; Morris Riedel, Kristel Michielsen, Gabriele Cavallaro, Forschungszentrum Jülich GmbH, Germany
Resources
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