High-Dimensional Data Analysis Laboratory

Publications

I. Horenko

Cheap robust learning of data anomalies with analytically solvable entropic outlier sparsification

Proceedings of the National Academy of Sciences (PNAS), Volume 119, Issue 9, Feb 2022, Pages 95-102, doi.org/10.1073/pnas.2119659119

I. Horenko, D. Rodrigues, T. O’Kane, K. Everschore-Sitte

Scalable computational measures for entropic detection of latent relations and their applications to magnetic imaging

Communications in Applied Mathematics and Computational Science, Volume 16, Number 2, Pages 267-297, doi.org/10.2140/camcos.2021.16.267

I. Horenko, L. Pospisil, E. Vecchi, S. Albrecht, A. Gerber, B. Rehbock, A. Stroh, S. Gerber

Quality-preserving low-cost probabilistic 3D denoising with applications to Computed Tomography

J.B. Isbister, V. Reyes-Puerta, J. Sun, I. Horenko, H.J. Luhmann

Clustering and control for adaptation uncovers time-warped spike time patterns in cortical networks in vivo

Scientific Reports, Volume 11, Number 1, 2021, Pages 1-20, doi.org/10.1038/s41598-021-94002-0

O. Kaiser, D. Igdalov, O. Martius, I. Horenko

On Computationally-Scalable Spatio-Temporal Regression Clustering of Precipitation Threshold Excesses

arXiv preprint arXiv:2103.16687, arxiv.org/abs/2103.16687

D. Röhe Rodrigues, K. Everschor-Sitte, S. Gerber, I. Horenko,

A deeper look into natural sciences with physics-based and data-driven measures

iScience, Volume 24, Issue 3, 2021, Pages 202171, doi.org/10.1016/j.isci.2021.102171

I. Horenko, G. Marchenko, P. Gagliardini

On a computationally-scalable sparse formulation of the multidimensional and non-stationary maximum entropy principle

Communications in Applied Mathematics and Computational Science, Volume 15, Number 2, Pages 1-38, 2020 https://msp.org/soon/coming.php?jpath=camcos

I. Horenko, D. Rodrigues, T. O'Kane, K. Everschor-Sitte

Physically-inspired computational tools for sharp detection of material inhomogeneities in magnetic imaging

I. Horenko

On a scalable entropic breaching of the overfitting barrier in machine learning

Neural Computation, Volume 32, Number 8, pages 1563-1579, 2020 www.mitpressjournals.org/toc/neco/32/8

S. Gerber, L. Pospisil, M. Navandar, I. Horenko

Low-cost scalable discretization, prediction and feature selection for complex systems.

Science Advances, Volume 6, Number 5, eaaw0961, 2020 DOI: 10.1126/sciadv.aaw0961

M. Rosenau, I. Horenko, F. Corbi, M. Rudolf, R. Kornhuber and O. Oncken

Synchronization of great subduction megathrust earthquakes: Insights from scale model analysis.

Journal of Geophysical Research: Solid Earth, 124(4):3646-3661, 2019 agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018JB016597

M. Rosenau, I. Horenko, F. Corbi, M. Rudolf, R. Kornhuber and O. Oncken

Synchronization of great subduction megathrust earthquakes: Insights from scale model analysis.

Journal of Geophysical Research: Solid Earth, 124(4):3646-3661, 2019 agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018JB016597