Research

Preprints

• A. Ringh, J. Karlsson, and A. Lindquist. An analytic interpolation approach to stability margins with emphasis on time delay. Submitted for publication.

Journal papers

• S. Banert, A. Ringh, J. Adler, J. Karlsson, O. Öktem. Data-driven nonsmooth optimization. Accepted to SIAM Journal on Optimization, 2019.
  [preprint] [code]
• S. Zhang, A. Ringh, X. Hu, and J. Karlsson. Modeling collective behaviors: A moment-based approach. Accepted to IEEE Transactions on Automatic Control, 2019.
  [preprint]
• A. Ringh, J. Karlsson, and A. Lindquist. Multidimensional Rational Covariance Extension with Approximate Covariance Matching. SIAM Journal on Control and Optimization, 2018.
  [preprint]
• J. Karlsson and A. Ringh. Generalized Sinkhorn iterations for regularizing inverse problems using optimal mass transport. SIAM Journal on Imaging Sciences, 2017.
  [preprint] [code (zip)] [code (github)]
• A. Ringh, J. Karlsson, and A. Lindquist. Multidimensional Rational Covariance Extension with Applications to Spectral Estimation and Image Compression. SIAM Journal on Control and Optimization, 2016.
  [preprint]
• J. Karlsson, A. Lindquist, and A. Ringh. The Multidimensional Moment Problem with Complexity Constraint. Integral Equations and Operator Theory, 2016.
  [preprint]

Conference papers (peer reviewed)

• I. Haasler, A. Ringh, Y. Chen, and J. Karlsson. Estimating ensemble flows on a hidden Markov chain . Accepted to IEEE Conference on Decision and Control (CDC), Dec. 2019.
  [preprint]
• A. Ringh, J. Karlsson, and A. Lindquist. Lower bounds on the maximum delay margin by analytic interpolation. IEEE Conference on Decision and Control (CDC), Dec. 2018.
  [preprint] [presentation]
• S. Zhang, A. Ringh, X. Hu, and J. Karlsson. A Moment-Based Approach to Modeling Collective Behaviors. IEEE Conference on Decision and Control (CDC), Dec. 2018.
  [preprint]
• A. Ringh, J. Karlsson, and A. Lindquist. Further results on multidimensional rational covariance extension with application to texture generation. IEEE Conference on Decision and Control (CDC), Dec. 2017.
  [preprint] [presentation]
• A. Ringh, X. Zhuge, W. J. Palenstijn, K. J. Batenburg, and O. Öktem. High-level algorithm prototyping: an example extending the TVR-DART algorithm. Discrete Geometry for Computer Imagery (DGCI), Sept. 2017.
  [preprint] [code (github)] [presentation]
• A. Ringh, J. Karlsson, and A. Lindquist. The Multidimensional Circulant Rational Covariance Extension Problem: Solutions and Applications in Image Compression. IEEE Conference on Decision and Control (CDC), Dec. 2015.
  [preprint]
• A. Ringh and J. Karlsson. A Fast Solver for the Circulant Rational Covariance Extension Problem. European Control Conference (ECC), July 2015. Won best student paper award.
  [preprint] [code(zip)]
• A. Ringh and A. Lindquist. Spectral estimation of periodic and skew periodic random signals and approximation of spectral densities. Chinese Control Conference (CCC), July 2014.

Manuscripts

• J. Adler, A. Ringh, O. Öktem, and J. Karlsson. Learning to solve inverse problems using Wasserstein loss. Presented at the workshop Optimal Transport & Machine Learning at the conference Advances in Neural Information Processing Systems (NIPS) 2017.
  [code]

Some other presentations (posters and slides)

• Seminar at INRIA Sophia-Antipolis 2018-07-03 - The multidimensional rational covariance extension problem.
• Seminar at INRIA Sophia-Antipolis 2018-06-21 - Optimal mass transport as a distance measure between images.
• Poster ERNSI 2017 - Texture generation and Wiener system identification by multidimensional rational covariance extension.
• Poster ERNSI 2016 - Multidimensional Rational Covariance Extension with Approximate Covariance Matching.

Thesis

• Multidimensional inverse problems in imaging and identification using low-complexity models, optimal mass transport, and machine learning. PhD thesis, KTH Royal Institute of Technology, 2018.
  [thesis] [DiVA]