Submitted:


 

  • DALnet: High-resolution photoacoustic projection imaging using deep learning
    J. Schwab, S. Antholzer, R. Nuster and M. Haltmeier
    Submitted, 2018 [pdf pdf button] [arxiv.org]
  • A New Sparsification and Reconstruction Strategy for Compressed Sensing Photoacoustic Tomography
    M. Haltmeier, M. Sandbichler, T. Berer, J. Bauer-Marschallinger, P. Burgholzer, L. Nguyen
    Submitted, 2018 [pdf pdf button] [arxiv.org]
  • A Framework for Compressive Time-of Flight 3D Sensing
    S. Antholzer, C. Wolf, M. Sandbichler, M. Dielacher and M. Haltmeier
    Submitted, 2017 [pdf pdf button] [arxiv.org]
  • The quasi-optimality criterion in the linear functional strategy
    S. Kindermann, S. Pereverzyev Jr., A. Pilipenko
    Submitted, 2017 [pdfpdf button] [arxiv.org]
  • Regularized Nyström subsampling in regression and ranking problems under general smoothness assumptions
    G.L. Myleiko, S. Pereverzyev Jr., S.G. Solodky
    Submitted, 2017 [pdfpdf button]
  • On the configuration space of planar Closed kinematic Chains
    G. Zangerl
    Submitted, 2017 [pdf  pdf button]
  • Operator learning approach for the limited view problem in photoacoustic tomography
    F. Dreier, S. Pereverzyev Jr., M. Haltmeier
    Submitted, 2017 [pdfpdf button] [arxiv.org]
  • Total Variation Minimization Compressed Sensing
    F. Krahmer, C. Kruschel, M. Sandbichler
    Submitted, 2017 [pdf pdf button] [arxiv.org]
  • Sequential Learning of Analysis Operators
    M. Sandbichler, K. Schnass
    Submitted, 2017 [pdf pdf button] [arxiv.org]
  • Dictionary Learning from Incomplete Data
    V. Naumova, K. Schnass
    Submitted, 2017 [pdf pdf button] [arxiv.org]
  • Deep Learning for Photoacoustic Tomography from Sparse Data
    S. Antholzer, M. Haltmeier, J. Schwab
    Submitted, 2017 [pdfpdf button] [arxiv.org]
  • A Machine Learning Framework for Customer Purchase Prediction in the Non-Contractual Setting
    A. Martínez, C. Schmuck, S. Pereverzyev Jr., C. Pirker, M. Haltmeier,
    Submitted, 2016 [pdf pdf button]
  • Convergence radius and sample complexity of ITKM algorithms for dictionary learning
    K. Schnass
    Submitted, 2016 [pdf pdf button]