Big in Japan: Regularizing Networks for Solving Inverse Problems
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DOI: 10.1007/s10851-019-00911-1
Abstract: Deep learning and (deep) neural networks are emerging tools to address inverse problems and image reconstruction tasks. Despite outstanding performance, the mathematical analysis for solving inverse problems by neural networks is mostly missing. In this… read more here.
Keywords: mathbf alpha; inverse problems; solving inverse; regularization ... See more keywords
Multi-atom quasiparticle scattering interference for superconductor energy-gap symmetry determination
Sign Up to like & getrecommendations! Published in 2020 at "npj Quantum Materials"
DOI: 10.1038/s41535-020-00303-4
Abstract: Complete theoretical understanding of the most complex superconductors requires a detailed knowledge of the symmetry of the superconducting energy-gap $${\mathrm{{\Delta}}}_{\mathbf{k}}^\alpha$$ Δ k α , for all momenta k on the Fermi surface of every band… read more here.
Keywords: mathbf alpha; energy; interference; mathrm delta ... See more keywords