1 citations · 1 across the 5 of their papers we have counts for
11 papers
Centering Ecological Goals in Automated Identification of Individual Animals
Lukas Picek, Timm Haucke, Lukáš Adam +16
Recognizing individual animals over time is central to many ecological and conservation questions, including estimating abundance, survival, movement, and social structure. Recent…
Split, Skip and Play: Variance-Reduced ProxSkip for Tomography Reconstruction is Extremely Fast
Evangelos Papoutsellis, Zeljko Kereta, Kostas Papafitsoros
Many modern iterative solvers for large-scale tomographic reconstruction incur two major computational costs per iteration: expensive forward/adjoint projections to update the data…
Deep unrolling for learning optimal spatially varying regularisation parameters for Total Generalised Variation
Thanh Trung Vu, Andreas Kofler, Kostas Papafitsoros
We extend a recently introduced deep unrolling framework for learning spatially varying regularisation parameters in inverse imaging problems to the case of Total Generalised Varia…
Learning Spatially Adaptive -Norms Weights for Convolutional Synthesis Regularization
Andreas Kofler, Luca Calatroni, Christoph Kolbitsch +1
We propose an unrolled algorithm approach for learning spatially adaptive parameter maps in the framework of convolutional synthesis-based regularization. More precisely,…
Why do we regularise in every iteration for imaging inverse problems?
Evangelos Papoutsellis, Zeljko Kereta, Kostas Papafitsoros
Regularisation is commonly used in iterative methods for solving imaging inverse problems. Many algorithms involve the evaluation of the proximal operator of the regularisation ter…
Nested Bregman Iterations for Decomposition Problems
Tobias Wolf, Derek Driggs, Kostas Papafitsoros +2
We consider the task of image reconstruction while simultaneously decomposing the reconstructed image into components with different features. A commonly used tool for this is a va…