Institution · Austrian Research Institute for Artificial Intelligence
Most cited papers from Austrian Research Institute for Artificial Intelligence
What are the most cited papers from Austrian Research Institute for Artificial Intelligence?
The most cited paper from Austrian Research Institute for Artificial Intelligence is "Learning in the Presence of Concept Drift and Hidden Contexts" (Gerhard Widmer, Miroslav Kubát, 1996), with 1,454 citations. Next come "Overview and Recent Advances in Partial Least Squares" (1,101) and "Deep Learning for Audio Signal Processing" (868).
Showing 50 of 58 papers. Every paper with more than 128 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Learning in the Presence of Concept Drift and Hidden Contexts Gerhard Widmer, Miroslav Kubát · Machine Learning | Apr 1996 | 1,454 |
| 2 | Overview and Recent Advances in Partial Least Squares Roman Rosipal, Nicole Krämer · Lecture notes in computer science | 2006 | 1,101 |
| 3 | Deep Learning for Audio Signal Processing H.‐G. Purwins, Bo Li, Tuomas I. Virtanen et al. · IEEE Journal of Selected Topics in Signal Processing | Apr 2019 | 868 |
| 4 | SpectralGPT: Spectral Remote Sensing Foundation Model Danfeng Hong, Bing Zhang, Xuyang Li et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence | 3 Apr 2024 | 848 |
| 5 | ERD/ERS patterns reflecting sensorimotor activation and deactivation Christa Neuper, Michael Wörtz, Gert Pfurtscheller · Progress in brain research | 2006 | 834 |
| 6 | High-content CRISPR screening Christoph Bock, Paul Datlinger, Florence M. Chardon et al. · Nature Reviews Methods Primers | 10 Feb 2022 | 603 |
| 7 | A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study Jesse Joachim Swen et al. · The Lancet | Feb 2023 | 564 |
| 8 | Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation Josine L. Min et al. · Nature Genetics | Sep 2021 | 554 |
| 9 | Separate-and-Conquer Rule Learning Johannes Fürnkranz · Artificial Intelligence Review | Feb 1999 | 531 |
| 10 | Interrater reliability for sleep scoring according to the Rechtschaffen & Kales and the new AASM standard Heidi Danker‐Hopfe, P. Anderer, Josef Zeitlhofer et al. · Journal of Sleep Research | 24 Feb 2009 | 421 |
| 11 | Towards a Common Framework for Multimodal Generation: The Behavior Markup Language Stefan Kopp, Brigitte Krenn, Stacy Marsella et al. · Lecture notes in computer science | 2006 | 410 |
| 12 | Sleep Classification According to AASM and Rechtschaffen & Kales: Effects on Sleep Scoring Parameters Doris Moser, P. Anderer, Georg B. Gruber et al. · SLEEP | Feb 2009 | 399 |
| 13 | Incremental Reduced Error Pruning Johannes Fürnkranz, Gerhard Widmer · Elsevier eBooks | 1994 | 367 |
| 14 | The pathophysiology of sepsis and precision-medicine-based immunotherapy Evangelos J. Giamarellos‐Bourboulis, Anna C. Aschenbrenner, Michael W Bauer et al. · Nature Immunology | 2024 | 365 |
| 15 | Hyperglycemia Induces Trained Immunity in Macrophages and Their Precursors and Promotes Atherosclerosis Laurienne Edgar et al. · Circulation | 13 Jul 2021 | 343 |
| 16 | Transfer learning using a multi-scale and multi-network ensemble for skin lesion classification Amirreza Mahbod, Gerald Schaefer, Chunliang Wang et al. · Computer Methods and Programs in Biomedicine | 21 Mar 2020 | 319 |
| 17 | An E-Health Solution for Automatic Sleep Classification according to Rechtschaffen and Kales: Validation Study of the Somnolyzer 24 × 7 Utilizing the Siesta Database P. Anderer, Georg B. Gruber, Silvia Parapatics et al. · Neuropsychobiology | 2005 | 298 |
| 18 | Detecting harmonic change in musical audio Christopher Harte, Mark B. Sandler, Martin Gasser | 27 Oct 2006 | 284 |
| 19 | Ultra-high-throughput single-cell RNA sequencing and perturbation screening with combinatorial fluidic indexing Paul Datlinger, André F. Rendeiro, Thorina Boenke et al. · Nature Methods | 31 May 2021 | 282 |
| 20 | Content-based organization and visualization of music archives Elias Pampalk, Andreas Rauber, Dieter Merkl | Dec 2002 | 277 |
| 21 | Brain-computer interfaces for 1-D and 2-D cursor control: designs using volitional control of the EEG spectrum or steady-state visual evoked potentials Leonard J. Trejo, Roman Rosipal, Bryan L. Matthews · IEEE Transactions on Neural Systems and Rehabilitation Engineering | Jun 2006 | 271 |
| 22 | An experimental comparison of audio tempo induction algorithms Fabien Gouyon, Anssi P. Klapuri, Simon Dixon et al. · IEEE Transactions on Audio Speech and Language Processing | 23 Aug 2006 | 257 |
| 23 | Mode choice, substitution patterns and environmental impacts of shared and personal micro-mobility Daniel Reck, Henry Martin, Kay Werner Axhausen · Transportation Research Part D Transport and Environment | 23 Dec 2021 | 254 |
| 24 | Chromatin accessibility profiling methods Liesbeth Minnoye, Georgi K. Marinov, Thomas Krausgruber et al. · Nature Reviews Methods Primers | 21 Jan 2021 | 232 |
| 25 | Pairwise Preference Learning and Ranking Johannes Fürnkranz, Eyke Hüllermeier · Lecture notes in computer science | 2003 | 230 |
| 26 | Interrater reliability between scorers from eight European sleep laboratories in subjects with different sleep disorders Heidi Danker‐Hopfe, Dieter Kunz, G. Gruber et al. · Journal of Sleep Research | 23 Feb 2004 | 222 |
| 27 | Landslide detection using deep learning and object-based image analysis Omid Ghorbanzadeh, Hejar Shahabi, Alessandro Crivellari et al. · Landslides | 20 Jan 2022 | 217 |
| 28 | Viral variant-resolved wastewater surveillance of SARS-CoV-2 at national scale Fabian Amman et al. · Nature Biotechnology | 18 Jul 2022 | 210 |
| 29 | Multimodal analysis of cell-free DNA whole-genome sequencing for pediatric cancers with low mutational burden Peter Peneder et al. · Nature Communications | 28 May 2021 | 208 |
| 30 | Landslide4Sense: Reference Benchmark Data and Deep Learning Models for Landslide Detection Omid Ghorbanzadeh, Yonghao Xu, Pedram Ghamisi et al. · IEEE Transactions on Geoscience and Remote Sensing | 2022 | 204 |
| 31 | Computational Models of Expressive Music Performance: The State of the Art Gerhard Widmer, Werner Goebl · Journal of New Music Research | Sep 2004 | 201 |
| 32 | Improved musical onset detection with Convolutional Neural Networks Jan Schlüter, Sebastian Böck | May 2014 | 199 |
| 33 | madmom Sebastian Böck, Filip Korzeniowski, Jan Schlüter et al. | 29 Sep 2016 | 194 |
| 34 | The SIESTA project polygraphic and clinical database G. Klosh, Bob Kemp, Thomas Penzel et al. · IEEE Engineering in Medicine and Biology Magazine | 2001 | 188 |
| 35 | Methods for the qualitative evaluation of lexical association measures Stefan Evert, Brigitte Krenn | 2001 | 188 |
| 36 | Artificial Neural Networks — ICANN 2001 Georg Dorffner, Kurt Hornik, Horst Bischof · Lecture notes in computer science | 2001 | 183 |
| 37 | Deep Learning and Earth Observation to Support the Sustainable Development Goals: Current approaches, open challenges, and future opportunities Claudio Persello, Jan Dirk Wegner, Ronny Hänsch et al. · IEEE Geoscience and Remote Sensing Magazine | 14 Jan 2022 | 182 |
| 38 | Acute BAF perturbation causes immediate changes in chromatin accessibility Sandra Schick, Sarah Grosche, Katharina Eva Kohl et al. · Nature Genetics | 8 Feb 2021 | 180 |
| 39 | Effective learning in dynamic environments by explicit context tracking Gerhard Widmer, Miroslav Kubát · Lecture notes in computer science | 1993 | 176 |
| 40 | Exploring Data Augmentation for Improved Singing Voice Detection with Neural Networks. Jan Schlüter, Thomas Grill | 26 Oct 2015 | 175 |
| 41 | The Organoid Cell Atlas the Human Cell Atlas ‘Biological Network’ Organoids, Christoph Bock, Michael Boutros et al. · Nature Biotechnology | 31 Dec 2020 | 173 |
| 42 | A Review of Automatic Rhythm Description Systems Fabien Gouyon, Simon Dixon · Computer Music Journal | Mar 2005 | 169 |
| 43 | A comprehensive transferability evaluation of U-Net and ResU-Net for landslide detection from Sentinel-2 data (case study areas from Taiwan, China, and Japan) Omid Ghorbanzadeh, Alessandro Crivellari, Pedram Ghamisi et al. · Scientific Reports | 16 Jul 2021 | 164 |
| 44 | Artifact Processing in Computerized Analysis of Sleep EEG – A Review P. Anderer, Stephen John Roberts, Alois Schlögl et al. · Neuropsychobiology | 1999 | 163 |
| 45 | Direct Effect of Sunshine on Suicide Benjamin Vyssoki, Nestor D. Kapusta, Nicole Praschak-Rieder et al. · JAMA Psychiatry | 10 Sep 2014 | 154 |
| 46 | The Digital Health Competencies in Medical Education Framework Josip Car et al. · JAMA Network Open | 31 Jan 2025 | 148 |
| 47 | A reliable probabilistic sleep stager based on a single EEG signal Arthur Flexer, Georg B. Gruber, Georg Dorffner · Artificial Intelligence in Medicine | 5 Aug 2004 | 147 |
| 48 | Telemedical support to improve glycemic control in adolescents with type 1 diabetes mellitus Birgit M. Rami-Merhar, Christian Popow, Werner Horn et al. · European Journal of Pediatrics | 2 May 2006 | 142 |
| 49 | Pruning Algorithms for Rule Learning Johannes Fürnkranz · Machine Learning | May 1997 | 139 |
| 50 | On the use of self-organizing maps for clustering and visualization Arthur Flexer · Intelligent Data Analysis | 19 Nov 2001 | 138 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for an institution when any of its authors gave it as an affiliation; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.