Kristian Bredies
Computational Mechanics · 2007–2018
A researcher in the Science corpus: 8 papers; trusts 36 researchers and is trusted by 29 researchers here, as inferred from the citation graph.
Subfields
- Computational Mechanics — 59 citations into it; #1,090 of 10,001 by trust here, #1,249 by citations
- Computer Vision and Pattern Recognition — 41 citations into it
- Mathematical Physics — 36 citations into it; #1,038 of 8,562 by trust here, #810 by citations
- Computational Theory and Mathematics — 14 citations into it; #3,305 of 12,182 by trust here, #6,463 by citations
- Applied Mathematics — 12 citations into it; #2,791 of 7,620 by trust here, #3,589 by citations
- Numerical Analysis — 12 citations into it
- Radiology, Nuclear Medicine and Imaging — 12 citations into it; #616 of 3,265 by trust here, #1,299 by citations
- Optimization & Training — 11 citations into it
Whom Kristian Bredies trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yurii E. Nesterov
- Ingrid Daubechies
- David L. Donoho
- Elena Resmerita
- Luigi Ambrosio
- Dirk A. Lorenz
- Michel Defrise
- E.J. Candes
- Bernd Hofmann
- Antonin Chambolle
Who trusts Kristian Bredies overall
- J. D. L. Reyes
- Martin Benning
- Carola-Bibiane Schönlieb
- Alekh Agarwal
- Markus Grasmair
- Vincent Duval
- Alireza Doostan
- Otmar Scherzer
- Konstantinos Papafitsoros
- Kerstin Hammernik
Papers from Kristian Bredies's perspective
Ordered by how strongly the researchers Kristian Bredies trusts endorse each paper. Same corpus, a different order for every researcher.
- An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
- Atomic Decomposition by Basis Pursuit
- Regression Shrinkage and Selection via the Lasso
- ImageNet classification with deep convolutional neural networks
- Stable signal recovery from incomplete and inaccurate measurements
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems (IEEE Journal on Selected Topics in Signal Processing)
- Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ1 minimization
Their papers
- Linear Convergence of Iterative Soft-Thresholding (2007) — 294 citations
- Regularization with non-convex separable constraints (2009) — 140 citations
- Sparsity of solutions for variational inverse problems with finite-dimensional data (2018) — 103 citations
- Regularization of linear inverse problems with total generalized variation (2014) — 90 citations
- Inverse problems in spaces of measures (2013) — 231 citations
- Properties of L1-TGV2: The one-dimensional case (2013) — 60 citations
- Second order total generalized variation (TGV) for MRI (2011) — 630 citations
- Total Generalized Variation (2010) — 1,593 citations