IDA LAB

INTELLIGENT DATA ANALYTICS SALZBURG

VORSPRUNG DURCH
ANGEWANDTE
FORSCHUNG IN
DATA SCIENCE,
KÜNSTLICHER
INTELLIGENZ,
STATISTIK

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News Overview

11 August 2026 | Pre-doctoral researcher in the AI-MINTFIT research project (Data Science / ML / Statistics)

Application deadline: 2 September 2026 Job type: Academic staff Start date: As soon as possible Further information: University of Salzburg job portal
Image: Summer School 2026

23–26 June 2026 | 10th Biostatistics Summer School

The 10th Biostatistics Summer School took place in Strobl from 23 to 26 June, with just under 30 international participants. In…
Flyer: 3rd RL Bootcamp

16–18 September 2026 | 3rd International Reinforcement Learning Bootcamp

Free three-day Reinforcement Learning Bootcamp at the University of Salzburg! Further information: 📅 Date: 16–18 September 2026 📍 Venue: Unipark Nonntal, University…
Picture Demos. - Uni. Salzburg

28.05.2026 | Together against university budget cuts

Image IDA Lab © IDA Lab Team ✊📢 IDA Lab on the way to the demonstration against massive budget cuts at the...
Image IDA Lab, Connecting Clusters

27.04.2026 | IDA Lab Salzburg presented as success story of the month April

Image IDA Lab © IDA Lab Team The IDA Lab Salzburg was recognised as a success story of the IDA Lab Salzburg as part of the Connecting...
Picture S. Hirländer

04.02.2026 | New podcast with Simon Hirländer

New podcast episode of EASY cheese DIGITAL.S2 #17 | Learning to make decisions: How reinforcement learning is changing organisations - with Simon...

28.01.2026 | PraeDoc in the research project KI - MINFIT (Data Science/ML/Statistics)

Application deadline: 25.02.2026Job type: Academic staffStart date: July 2026 Further information: University of Salzburg job portal
Picture Uki

19.01.2026 | Research cooperation: Article „Climate adaptation in the rock crevice“

© Ulrike Ruprecht/Uni Salzburg Successful research cooperation within the Paris Lodron University of Salzburg (PLUS) in the project LIVE: Lichen holobiont diversity along climatic...

17 December 2025 | Adaptive Learning Algorithms in Control Systems

Published in COPA-DATA Magazine Information Unlimited, Issue #44

30.03. - 01.04.2026 | 4th Collaboration Workshop on Reinforcement Learning for Autonomous Accelerators (RL4AA’26)

The Reinforcement Learning for Autonomous Accelerators (RL4AA) Collaboration invites you to the fourth workshop: RL4AA’26. The event is organised in cooperation with...

30 - 31 Oct 2025 | STEAM for tomorrow: From Erasmus + outcomes to skills and policy in higher education

Picture IDA Lab © IDA Lab Team Our colleagues from the IDA Lab had the pleasure of attending the STEAM Conference 2025...
Picture press release: UniSbg & PHSbg

21.10.2025 | Press release: „Educational innovation needs educational research“

© AI-generated image Joint cooperation between the University of Salzburg and the Salzburg University of Teacher Education (PH Salzburg) - funded by BMFWF...

11 August 2026 | Pre-doctoral researcher in the AI-MINTFIT research project (Data Science / ML / Statistics)

Application deadline: 2 September 2026 Job type: Academic staff Start date: As soon as possible Further information: University of Salzburg job portal
Image: Summer School 2026

23–26 June 2026 | 10th Biostatistics Summer School

The 10th Biostatistics Summer School took place in Strobl from 23 to 26 June, with just under 30 international participants. In…
Flyer: 3rd RL Bootcamp

16–18 September 2026 | 3rd International Reinforcement Learning Bootcamp

Free three-day Reinforcement Learning Bootcamp at the University of Salzburg! Further information: 📅 Date: 16–18 September 2026 📍 Venue: Unipark Nonntal, University…
Picture Demos. - Uni. Salzburg

28.05.2026 | Together against university budget cuts

Image IDA Lab © IDA Lab Team ✊📢 IDA Lab on the way to the demonstration against massive budget cuts at the...
Image IDA Lab, Connecting Clusters

27.04.2026 | IDA Lab Salzburg presented as success story of the month April

Image IDA Lab © IDA Lab Team The IDA Lab Salzburg was recognised as a success story of the IDA Lab Salzburg as part of the Connecting...
Picture S. Hirländer

04.02.2026 | New podcast with Simon Hirländer

New podcast episode of EASY cheese DIGITAL.S2 #17 | Learning to make decisions: How reinforcement learning is changing organisations - with Simon...

28.01.2026 | PraeDoc in the research project KI - MINFIT (Data Science/ML/Statistics)

Application deadline: 25.02.2026Job type: Academic staffStart date: July 2026 Further information: University of Salzburg job portal
Picture Uki

19.01.2026 | Research cooperation: Article „Climate adaptation in the rock crevice“

© Ulrike Ruprecht/Uni Salzburg Successful research cooperation within the Paris Lodron University of Salzburg (PLUS) in the project LIVE: Lichen holobiont diversity along climatic...

17 December 2025 | Adaptive Learning Algorithms in Control Systems

Published in COPA-DATA Magazine Information Unlimited, Issue #44

30.03. - 01.04.2026 | 4th Collaboration Workshop on Reinforcement Learning for Autonomous Accelerators (RL4AA’26)

The Reinforcement Learning for Autonomous Accelerators (RL4AA) Collaboration invites you to the fourth workshop: RL4AA’26. The event is organised in cooperation with...

30 - 31 Oct 2025 | STEAM for tomorrow: From Erasmus + outcomes to skills and policy in higher education

Picture IDA Lab © IDA Lab Team Our colleagues from the IDA Lab had the pleasure of attending the STEAM Conference 2025...
Picture press release: UniSbg & PHSbg

21.10.2025 | Press release: „Educational innovation needs educational research“

© AI-generated image Joint cooperation between the University of Salzburg and the Salzburg University of Teacher Education (PH Salzburg) - funded by BMFWF...

11 August 2026 | Pre-doctoral researcher in the AI-MINTFIT research project (Data Science / ML / Statistics)

Application deadline: 2 September 2026 Job type: Academic staff Start date: As soon as possible Further information: University of Salzburg job portal
Image: Summer School 2026

23–26 June 2026 | 10th Biostatistics Summer School

The 10th Biostatistics Summer School took place in Strobl from 23 to 26 June, with just under 30 international participants. In…
Flyer: 3rd RL Bootcamp

16–18 September 2026 | 3rd International Reinforcement Learning Bootcamp

Free three-day Reinforcement Learning Bootcamp at the University of Salzburg! Further information: 📅 Date: 16–18 September 2026 📍 Venue: Unipark Nonntal, University…
Picture Demos. - Uni. Salzburg

28.05.2026 | Together against university budget cuts

Image IDA Lab © IDA Lab Team ✊📢 IDA Lab on the way to the demonstration against massive budget cuts at the...
Image IDA Lab, Connecting Clusters

27.04.2026 | IDA Lab Salzburg presented as success story of the month April

Image IDA Lab © IDA Lab Team The IDA Lab Salzburg was recognised as a success story of the IDA Lab Salzburg as part of the Connecting...
Picture S. Hirländer

04.02.2026 | New podcast with Simon Hirländer

New podcast episode of EASY cheese DIGITAL.S2 #17 | Learning to make decisions: How reinforcement learning is changing organisations - with Simon...

28.01.2026 | PraeDoc in the research project KI - MINFIT (Data Science/ML/Statistics)

Application deadline: 25.02.2026Job type: Academic staffStart date: July 2026 Further information: University of Salzburg job portal
Picture Uki

19.01.2026 | Research cooperation: Article „Climate adaptation in the rock crevice“

© Ulrike Ruprecht/Uni Salzburg Successful research cooperation within the Paris Lodron University of Salzburg (PLUS) in the project LIVE: Lichen holobiont diversity along climatic...

17 December 2025 | Adaptive Learning Algorithms in Control Systems

Published in COPA-DATA Magazine Information Unlimited, Issue #44

30.03. - 01.04.2026 | 4th Collaboration Workshop on Reinforcement Learning for Autonomous Accelerators (RL4AA’26)

The Reinforcement Learning for Autonomous Accelerators (RL4AA) Collaboration invites you to the fourth workshop: RL4AA’26. The event is organised in cooperation with...

30 - 31 Oct 2025 | STEAM for tomorrow: From Erasmus + outcomes to skills and policy in higher education

Picture IDA Lab © IDA Lab Team Our colleagues from the IDA Lab had the pleasure of attending the STEAM Conference 2025...
Picture press release: UniSbg & PHSbg

21.10.2025 | Press release: „Educational innovation needs educational research“

© AI-generated image Joint cooperation between the University of Salzburg and the Salzburg University of Teacher Education (PH Salzburg) - funded by BMFWF...

Events

Upcoming

16.09.26 - 18.09.26
11:00 - 17:00
Bootcamp
3rd International Reinforcement Learning Bootcamp
11:00 - 17:00
16.09.26 - 18.09.26
Bootcamp
3rd International Reinforcement Learning Bootcamp

Where: Unipark Nonntal, University of Salzburg, Austria
Costs: Free of charge (registration required – limited number of places!)

Organised by:
– The SARL team at the IDA Lab in Salzburg
in collaboration with:
– AI Austria
– JOANNEUM RESEARCH DIGITAL
– JOANNEUM RESEARCH ROBOTICS
– DIH West

Flyer: 3rd RL Bootcamp
10.07.26 - 11.07.26
8:00 - 17:00
Conference
10th BFF Conference: Bayesian, Fiducial and Frequentist Statistics
8:00 - 17:00
10.07.26 - 11.07.26
Conference
10th BFF Conference: Bayesian, Fiducial and Frequentist Statistics
Natural Sciences (University of Salzburg)

Scientific Committee:
Arne Bathke, Chair (University of Salzburg)
Minge Xie, Chair (Rutgers University)

With the support of the other members of the Scientific Committee

Ort:
Hellbrunner Street 34
5020 Salzburg
06.07.26 - 09.07.26
9:00 - 19:00
Conference
IMS Annual Meeting 2026
9:00 - 19:00
06.07.26 - 09.07.26
Conference
IMS Annual Meeting 2026
Salzburg Congress

Organised by:
Kavita Ramanan, IMS President
Genevera Allen, Programme Chair (Statistics)
Remco van der Hofstad, Programme Chair (Probability)
Arne Bathke, Local Host Programme Chair
Wolfgang Trutschnig, Session Chair

Ort:
Auerspergstrasse 6
5020 Salzburg
23.06.26 - 26.06.26
14:00 - 12:30
Summer School
Evaluation of Surrogate Endpoints in Clinical Trials
Arne Bathke
14:00 - 12:30
23.06.26 - 26.06.26
Summer School
Evaluation of Surrogate Endpoints in Clinical Trials
Arne Bathke
Federal Institute for Adult Education (bifeb)

Organised by Arne Bathke with the support of Georg Zimmermann and Minge Xie

In partnership with the professional associations ÖSG, IBS-DR and ROeS

Ort:

Strobl
17.06.26
9:00 - 12:30
Workshop
From data to insights: Your introduction to data science and AI
9:00 - 12:30
17.06.26
Workshop
From data to insights: Your introduction to data science and AI
Techno Z

This course is ideal for small and medium-sized companies looking for a practical and understandable introduction to data science and AI. You will learn how to better understand and analyse company data and how to use it specifically for data-based decisions.

Please bring your own laptop!

Techno-Z, Jakob-Haringer-Straße 5, 5020 Salzburg, seminar room C

For further information and/or to register, please click on the button „Log in“.

Ort:
Jakob-Haringer-Strasse 5
5020 Salzburg
10.03.26
9:00 - 12:00
Workshop
Better decisions through agentic AI
9:00 - 12:00
10.03.26
Workshop
Better decisions through agentic AI
Techno Z

Practical course for small and medium-sized companies: Learn how to use AI and autonomous systems in a targeted manner to make data-based decisions and organise processes more efficiently.

💻 Please bring your own laptop!

Event centre Techno-Z, Jakob Haringer Straße 5, 5020 Salzburg

Ort:
Jakob-Haringer-Strasse 5
5020 Salzburg

Applied Research

DS STIWA: Data Science STIWA

Paracelsus Medical University (PMU), House C, Strubergasse 22
Organiser: IDA Lab Team Biostatistics and Big Medical Data / Research Programme Biomedical Data Science.
Registration is free of charge, please contact  here register!

Applied Research

DS STIWA: Data Science STIWA

Paracelsus Medical University (PMU), House C, Strubergasse 22
Organiser: IDA Lab Team Biostatistics and Big Medical Data / Research Programme Biomedical Data Science.
Registration is free of charge, please contact  here register!

About
IDA LAb SAlzburg

Information on

The IDA Lab Salzburg (Lab for Intelligent Data Analytics), funded by the state of Salzburg as part of WISS 2025, is a competence centre for basic and applied research, as well as for knowledge and technology transfer in the fields of data science, machine learning, AI and statistics.

Cooperations & Projects

Ongoing projects

Smart Tourism Hub | PI: A. Bathke

Research co-operation with iSPACE plus GmbH/Salzburg research and the Paris Lodron University Salzburg (PLUS) / Dept. of Artificial Intelligence & Human Interfaces | funded by European Regional Development Fund | Applied Research | PLUS Research

Term: 01.05.2026 - 31.12.2028

Arne Bathke (Project management, PLUS), Thomas Prinz (Co-project management, PLUS)

INSPIRE: Intelligent Novel Support for Personalised Instruction and Robust Evaluation in STEM Lessons at Primary School | PI: S. Hirländer

Research co-operation with Salzburg University of Teacher Education (PH Salzburg) and the Paris Lodron University Salzburg (PLUS) / Department of Artificial Intelligence & Human Interfaces | funded by the Province of Salzburg (WISS2030) | Application-oriented basic research | PLUS Research

Homepage INSPIRE

Term: 01.01.2026 - 31.12.2028

Christina Egger (project management, PH Salzburg), Simon Hirländer (PLUS), Olga Mironova (Research assistant, PLUS), Markus Dygruber (Predoc, PLUS)

FOCUS: Forecasting and optimisation under constraints and uncertainty for sustainable industrial energy systems | PI: S. Hirländer

Research co-operation with Ing. Punzenberger COPA-DATA GmbH and the Paris Lodron University Salzburg (PLUS) / Dept. of Artificial Intelligence & Human Interfaces | funded by COPA-DATA GmbH | Application-oriented basic research | PLUS Research

Term: 01.10.2025 - 30.09.2028

Simon Hirländer (Project management, PLUS), Sarah Trausner (Predoc, PLUS)

Data Science PhD student II | PI: W. Trutschnig

Research co-operation with Red Bull GmbH and the Paris Lodron University Salzburg (PLUS) / FB Artificial Intelligence & Human Interfaces | funded by Red Bull GmbH I Application-orientated basic research | PLUS Research 

Term: 01.10.2025 - 30.09.2028

Wolfgang Trutschnig (Project management, PLUS)

KI-MINTFIT I: KI-MINTFIT Expertise through Innovation and Technology I | PI: A. Bathke

Research co-operation with Salzburg University of Education Stefan Zweig and the Paris Lodron University Salzburg (PLUS) / Dept. of Artificial Intelligence & Human Interfaces | funded by BM Education and BM Women, Science and Research | Applied Research | PLUS Research

Term: 01.10.2025 - 30.09.2028

Arne Bathke (Project management, PLUS), Ulrike Ruprecht (Co-project management, PLUS), Simon Hirländer (PLUS), Georg Zimmermann (PMU)

KRONUS: Continuous ROL process optimisation for sustainable US scrap reduction | PI: W. Trutschnig

Research co-operation with Austria Metall AG (AMAG) and the Paris Lodron University Salzburg (PLUS) / FB Artificial Intelligence & Human Interfaces | funded by the AMAG | Application-orientated basic research PLUS Research

Term: 01.09.2025 - 31.08.2028

Wolfgang Trutschnig (Project management, PLUS), Patrick Langthaler (Predoc, PLUS)

DIH-West: Digital Innovation Hub West | PI: A. Bathke

Partner consortium of universities and interest groups in Vorarlberg, Tyrol, Salzburg and the Paris Lodron University Salzburg (PLUS) / FB Artificial Intelligence & Human Interfaces | funded by the FFG and the State of Salzburg | Knowledge and Technology Transfer | PLUS Research

Term: 01.03.2024 - 29.02.2028

Arne Bathke (Project management, PLUS), Wolfgang Trutschnig (PLUS)

Completed projects

ReDim: Quantification of dependencies via dimensional reduction | PI: S. Fuchs

Individual project at the Paris Lodron University Salzburg (PLUS) / FB Artificial Intelligence & Human Interfaces | funded by the FWF Austrian Science Fund | Basic Research | PLUS Research

Term: 01.10.2022 - 31.08.2026

Sebastian Fuchs (Project management, PLUS), Yuping Wang (Predoc, PLUS), Carsten Limbach (Predoc, PLUS)

MuT IV: Patterns in tourism - weather, guest cards and more | PI: W. Trutschnig

Research co-operation with feratel media technologies AG and the Paris Lodron University Salzburg (PLUS) / Dept. of Artificial Intelligence & Human Interfaces | funded by feratel media technologies AG | Contract research PLUS Research

Term: 01.04.2026 - 31.08.2026

Wolfgang Trutschnig (Project management, PLUS), Sebastian Heintze (Postdoc, PLUS), Jonathan Faust (Master's student, PLUS), Michael Moisl (Master's student, PLUS)

PAS: Price Affinity and Sensitivity | PI: W. Trutschnig

Research co-operation with Raiffeisenverband Salzburg eGen and the Paris Lodron University Salzburg (PLUS) / Dept. of Artificial Intelligence & Human Interfaces | funded by Raiffeisenverband Salzburg eGen | Contract research PLUS Research

Term: 01.03.2026 - 31.08.2026

Wolfgang Trutschnig (Project management, PLUS), Arne Bathke (PLUS), Lea Maislinger (Predoc, PLUS), Kai Schärer (Predoc, PLUS)

publiCations

Research

2026

[204] D. Kokol Bukovšek, N. Stopar, W. Trutschnig: How far are 𝑑-dimensional copulas with uniform (𝑑−1)-marginals from (total) independence?. (2026) https://doi.org/10.1016/j.spl.2026.110948

[203] S. Appel, H. Alsmeier, M. Bajzek, O. Boine-Frankenheim, L. Dingeldein, R. Findeisen, B. Halilovic, S. Hirländer: Automating Accelerator Tuning at GSI/FAIR. (2026) https://doi.org/10.1007/s41781-026-00175-6

[202] S. Hirländer, O. Mironova, S. Trausner, L. Grech, L. Fischl, A. Santamaria Garcia: Koopman-Stabilised World Models for Offline Reinforcement Learning in Accelerator Control. (2026) https://doi.org/10.18429/JACoW-IPAC2026-WEP6098

[201] S. Hirländer, K. Björkbom, S. Trausner, O. Mironova, L. Fischl, P. Auer, R. Ortner, V. Kain: Reinforcement Learning Beyond Greedy Optimisation for Accelerator Control with Delayed Consequences. (2026) https://doi.org/10.18429/JACoW-IPAC2026-WEP6097

[200] S. Hirländer, O. Mironova, S. Trausner, L. Fischl, T. Gallien, L. Grech: Causal GP-MPC: Where Structure, Safety and Online Learning Come Together for Robust Accelerator Control. (2026) https://doi.org/10.18429/JACoW-IPAC2026-WEP6096

[199] S. Hirländer, B. Halilovic, P. Madysa, S. Appel: Robust real-time optimisation of SIS18 injection using Gaussian Process MPC. (2026) https://doi.org/10.18429/JACoW-IPAC2026-THP4097

[198] H. Kaiser, W. Trutschnig: On Bertino copulas and the Markov product. (2026) https://doi.org/10.1016/j.jmaa.2026.130572

[197] J. AnsariM. Rockel: The exact region and an inequality between Chatterjee's and Spearman's rank correlations. (2026) https://doi.org/10.1016/j.jmva.2026.105630

[196] N. Dietrich: On bivariate Archimax copulas: Level sets, mass distributions and related results. (2026) https://doi.org/10.1007/s10687-025-00523-6

[195] L. Maislinger, W. Trutschnig: Multivariate Archimedean copulas with fractal support. (2026) https://doi.org/10.1016/j.spl.2026.110692

[194] N. Dietrich, W. Trutschnig: On differentiability and mass distributions of multivariate Archimedean copulas. (2026) https://doi.org/10.1016/j.jmaa.2026.130523

[193] S. Fox, K. D. Schmidt, Y. Wang: A Note on Bertino and Fredricks-Nelsen Copulas. (2026) https://doi.org/10.1016/j.fss.2026.109846

[192] S. Fox, C. Limbach: A dimension reduction for extreme types of directed dependence. (2026) https://doi.org/10.1515/demo-2025-0016

[191] J. Ansari, P. Langthaler, S. Fox, W. Trutschnig: Quantifying and estimating dependence via sensitivity of conditional distributions. (2026) https://doi.org/10.3150/25-BEJ1854

[190] B. Strasser-Kirchweger, R. Kutil, G. Carpenter, C. Borgelt, W. Trutschnig, F. Hutzler: Machine-actionable criteria map the symptom space of mental disorders. (2026) https://doi.org/10.1038/s41746-026-02451-6

2025

[189] A. Götz, M. Andreev, R. R. Junker, L. Maislinger, L. G. Sancho, W. Trutschnig, U. Ruprecht: Future Range Shifts and Diversity Patterns of Antarctic Lecideoid Lichens Under Climate Change Scenarios. (2025) https://doi.org/10.1002/gcb4.70000

[188] J. Ansari, E. Lütkebohmert: Robust Bernoulli Mixture Models for Credit Portfolio Risk. (2025) https://doi.org/10.1111/mafi.70020

[187] S. Fox, C. Limbach, F. Schürrer: On exact regions between measures of concordance and Chatterjee's rank correlation for lower semilinear copulas. (2025) https://doi.org/10.1016/j.ijar.2025.109588

[186] H. Kaiser: An asymptotic expansion for the Mellin transform of a beta function and applications. (2025) https://doi.org/10.1080/10652469.2025.2565257

[185] G. B. Bottini, W. Lauth, W. Hitzl, B. Walch, et al.: Is there an „ideal“ sequence for open reduction and internal fixation of multiple mandibular fractures involving the condylar neck? A retrospective cohort study. (2025) https://doi.org/10.3390/jcm14207142

[184] R. Dey, A. Bathke, S. Kumar: Inference on overlap index: with an application to cancer data. (2025) https://doi.org/10.1515/ijb-2024-0106

[183] S. Clemens, C. Simon, W. Lauth, O. Rose, G. Carpenter, et al: Development and validation of a risk prediction tool for drug-related problems in pre-operative elective surgical patients (mediPORT): A case-control study. (2025) https://doi.org/10.1371/journal.pone.0326088

[182] B. Taxer, W. Lauth, H. von Piekartz, E. Trinka, S. Leis: Investigation of Sensory and Neuropsychological Parameters in Migraine Sufferers: A Cross-Sectional Study with Negative Findings. (2025) https://doi.org/10.1007/s40120-025-00824-9

[181] M. Delporte, J. Verbeck, I. Brambilla, G. Carpenter, G. Molenberghs, et al.: Dravet syndrome: Insights into seizure and speech progression from registry data. (2025) https://doi.org/10.1016/j.yebeh.2025.110459

[180] K. E. Thiel, P. Sattler, A. Bathke, G. Carpenter: Resampling NANCOVA: Nonparametric analysis of covariance in small samples. (2025) https://doi.org/10.1016/j.csda.2025.108290

[179] M. Kiefel, G. Gruber, D. Lahnsteiner, T. Prince: Spatiotemporal variability of passenger distribution to destination regions using the example of Salzburg Airport. (2025) https://doi.org/10.25598/agit/2025-29

[178] H. Sterzik, J. Arand, C. E. Schwarz, M. Kumpf, M. Wald, A. Kribs, W. Lauth, et al: Imposed work of breathing of 16 neonatal CPAP devices using different mechanisms of CPAP generation. (2025) https://doi.org/10.1038/s41390-025-04265-w

[177] S. Laner-Plamberger, A. Siller, W. Lauth, J.M. Kern, et al.: Stable SARS-CoV-2 antibody levels and functionality in serum and COVID-19 convalescent plasma after long-term storage. (2025) https://doi.org/10.1111/vox.70059

[176] J. Verbeeck, M. Geroldinger, J. Nyberg, K. E. Thiel, A. Bathke, G. Carpenter, et al: Reflection on clinical and methodological issues in rare disease clinical trials. (2025) https://doi.org/10.1186/s13023-025-03805-1

[175] B. Walch, A. Gaggl, G. B. Bottini, M. Geroldinger, et al: Comparison of Anatomical Maxillary Sinus Implant and Polydioxanone Sheets in Treatment of Orbital Floor Blowout Fractures: A Retrospective Cohort Study. (2025) https://doi.org/10.3390/jfb16060204

[174] S. Schaible, E. Hofstätter, W. Lauth, M. Wald: The Effect of the COVID-19 Pandemic and the Establishment of a Ronald McDonald House on Skin-to-Skin Times in the Neonatal Intensive Care Unit: A Retrospective Study. (2025) https://doi.org/10.3390/children12060803

[173] V. Wally, T. Welponer, H. P. Wiesinger, A. Diem, K. Thiel, M. Geroldinger, G. Carpenter, et al: Keratin-associated epidermolysis bullosa simplex: phenotypes and challenges in clinical trials – a narrative review and systematic update. (2025) https://doi.org/10.1186/s13023-025-03822-0

[172] J. F. Sánchez, W. Trutschnig: On bivariate Archimedean copulas with fractal support. (2025) https://doi.org/10.1515/demo-2025-0013

[171] M. Laimer, A. P. South, E. Mayer, S. Kitzmueller, L. Banner, M. A. Hosler, G. Carpenter, et al: Efficacy and safety of rigosertib in patients with recessive dystrophic epidermolysis bullosa-associated advanced/metastatic cutaneous squamous cell carcinoma. (2025) https://doi.org/10.1093/bjd/ljaf205

[170] M. C. Hribljan, G. Carpenter, S. Beniczky: Lateralising value of ictal head turning: A systematic review and meta-analysis. (2025) https://doi.org/10.1002/epd2.70046

[169] J. Ansari, M. Ritter: Comparison results forpositive supermodular dependent Markov tree distributions. (2025) https://doi.org/10.1214/25-EJS2465

[168] L. Maislinger, W. Trutschnig: On bivariate lower semilinear copulas and the star product. (2025) https://doi.org/10.1016/j.ijar.2025.109366

[167] F. Durante, S. FoxR. Pappadà: Clustering of compound events based on multivariate comonotonicity. (2025) https://doi.org/10.1016/j.spasta.2025.100881

[166] M. Oeller, O. Kartal, I. Trifonova, N. Held, W. Lauth, et al: Long-term retrospective analysis of parvovirus B19 infections in blood donors (2012–2014): significant increase in prevalence following the SARS-CoV-2 pandemic. (2025) https://doi.org/10.3390/diagnostics15182313

[165] M. TschimpkeM. Schreyer, W. Trutschnig: Revisiting the region determined by Spearman's ρ and Spearman's footrule ϕ. (2025) https://doi.org/10.1016/j.cam.2024.116259

[164] J. Beck, P. Langthaler, A. Bathke: Combining stochastic tendency and distribution overlap towards improved nonparametric effect measures and inference. (2025) https://doi.org/10.1111/sjos.12783

[163] A. E. Carrozzo, G. Carpenter, A. Bathke, D. Neunhaeuserer, et al.: Two-arm crossover randomised controlled trial versus meta-analysis of N-of-1 studies: comparison of statistical efficiency in determining an intervention effect. (2025) https://doi.org/10.1002/bimj.70045

[162] A. Kovács-GyőriD. Lahnsteiner, J. Schmitt, T. Prince: Spatiotemporal clustering based on internationaltourists' overnight stay data in Salzburg, Austria: aseasonal analysis using space-time data cubes toenhance airport connectivity. (2025) https://doi.org/10.1080/02508281.2024.2443728

[161] N. Dietrich, W. Trutschnig: On differentiability and mass distributions of typical bivariate copulas. (2025) https://doi.org/10.1016/j.fss.2024.109150

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2024

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2023

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2022

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2021

[52] M. Wagner, G. Brunauer, A. BathkeS.C. Cary, R. Fuchs, L.G. Sancho, R. Türk, U. Ruprecht: Macroclimatic conditions as main drivers for symbiotic association patterns in lecideoid lichens along the Transantarctic Mountains, Ross Sea region, Antarctica. (2021) https://doi.org/10.1038/s41598-021-02940-6

[51] A. Astner-Rohracher, G. Carpenter, T. Avigdor, et al: Development and Validation of the 5-SENSE Score to Predict Focality of the Seizure-Onset Zone as Assessed by Stereoelectroencephalography. (2021) https://doi.org/10.1001/jamaneurol.2021.4405

[50] V. Kain, N. Bruchon, S. HirländerN. Madysa, I. Vojskovic, P.K. Skowronski, G. Valentino: Test of Machine Learning at the Cern LINAC4. (2021) https://doi.org/10.18429/JACoW-HB2021-TUEC4

[49] T. Kasper, S. Fox, W. Trutschnig: On weak conditional convergence of bivariate Archimedean and Extreme Value copulas, and consequences to nonparametric estimation. (2021) https://doi.org/10.3150/20-BEJ1306

[48] A. Egger-Rainer, S.M. Hettegger, R. Feldner, S. Arnold, C. Bosselmann, H. Hamer, A. Hengsberger, J. Lang, S. Lorenzl, H. Lerche, S. Noachtar, E. Pataraia, A. Schulze-Bonhage, A.M. Staack, E. Trinka, I. Unterberger, G. Carpenter: Do all patients in the epilepsy monitoring unit experience the same level of comfort? A quantitative exploratory secondary analysis. (2021) https://doi.org/10.1111/jan.15105

[47] F. Petersen, C. BorgeltH. Kuehne, O. Deussen: Learning with Algorithmic Supervision via Continuous Relaxation. (2021) https://doi.org/10.48550/arXiv.2110.05651

[46] G. CarpenterE. Brunner, W. Brannath, M. Happ, A. Bathke: Pseudo Ranks: The Better Way of Ranking?. (2021) https://doi.org/10.1080/00031305.2021.1972836

[45] T. Kasper, S. Fox, W. Trutschnig: On convergence of associative copulas and related results. (2021) https://doi.org/10.1515/demo-2021-0114

[44] F. Kröger, G. Weber, S. HirländerR. Alemany-Fernández, M. W. Krasny, T. Stohlker, I. Tolstikhina, V. Shevelko: Charge-state distributions of highly charged lead ions at relativistic collision energies. (2021) https://doi.org/10.1002/andp.202100245

[43] E. Gfrerer, D. Laina, G. Danae, M. Gibernau, R. Fuchs, M. HappT. Tolasch, W. TrutschnigA.C. Hörger, H.P. Comes, S. Dötterl: Floral scents of a deceptive plant are hyperdiverse and under population-specific phenotypic selection. (2021) https://doi.org/10.3389/fpls.2021.719092

[42] T. Kovács, A. Kovács-GyőriB. Resch: #AllforJan: How Twitter Users in Europe Reacted to the Murder of Ján Kuciak-Revealing Spatiotemporal Patterns through Sentiment Analysis and Topic Modelling. (2021) https://www.mdpi.com/2220-9964/10/9/585#

[41] J.M. Berger, M. Gansterer, W. Trutschnig, A. Bathke, et al: SARS-CoV-2 screening in cancer outpatients during the second wave of the COVID-19 pandemic. (2021) https://doi.org/10.1007/s00508-021-01927-7

[40] J. Suárez-Varela, M. Ferriol-Galmés, A. López, P. Almasan, G. Bernárdez, D. Pujol-Perich, K. Rusek, L. Bonniot, C. Neumann, F. Schnitzler, F. Taïani, M. Happ, C. MaierJ. Lei Du, M. Herlich, P. Dorfinger, N.V. Hainke, S. Venz, J. Wegener, H. Wissing, B. Wu, S. Xiao, P. Barlet-Ros, A. Cabellos-Aparicio: The Graph Neural Networking Challenge: A Worldwide Competition for Education in AI/ML for Networks. (2021) https://doi.org/10.1145/3477482.3477485

[39] M. Happ, M Marvellous, C. MaierJ. L. Du, P. Dorfinger: Graph-neural-network-based delay estimation for communication networkswith heterogeneous scheduling policies. (2021) https://doi.org/10.52953/TEJX5530

[38] L. Weidner, V. Nunhofer, C. Jungbauer, A.D. Hoeggerl, L. Grüner, C. Grabmer, G. CarpenterE. Rohde, S. Laner-Plamberger: Seroprevalence of anti-SARS-CoV-2 total antibody is higher in younger Austrian blood donors. (2021) https://doi.org/10.1007/s15010-021-01639-0

[37] F. Konietschke, C. Cao, A. Gunawardana, G. Carpenter: Analysis of covariance under variance heteroscedasticity in general factorial designs. (2021) https://doi.org/10.1002/sim.9092

[36] N. Bruchon, G. Fenu, G. Gaio, S. HirländerM. Lonza, F.A. Pellegrino, E. Salvato: An Online Iterative Linear Quadratic Approach for a Satisfactory Working Point Attainment at FERMI. (2021) https://doi.org/10.3390/info12070262

[35] F. Petersen, C. BorgeltH. Kuehne, O. Deussen: Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision. (2021) https://doi.org/10.48550/arXiv.2105.04019

[34] A. Bathke, M. HappM. Hummer: Indirect vaccination effects for children and adolescents when adults are fully vaccinated. (2021) Executive Policy Brief

[33] J. Pilz, L. Hehenwarter, G. CarpenterG. Rendl, G. Schweighofer-Zwink, M. Beheshti, C. Pirich: Feasibility of equivalent performance of 3D TOF [18F]-FDG PET/CT with reduced acquisition time using clinical and semiquantitative parameters. (2021) https://doi.org/10.1186/s13550-021-00784-9

[32] A. Schenk, M. Neuhäuser, G.D. Ruxton, A. Bathke: Predictors of pre-European deforestation on Pacific islands: A re-analysis using modern multivariate non-parametric statistical methods. (2021) https://doi.org/10.1016/j.foreco.2021.119238

[31] V. Racher, C. Borgelt: Gradient Ascent for Best Response Regression. (2021) https://doi.org/10.1007/978-3-030-74251-5_12

[30] T. Mroz, S. Fox, W. Trutschnig: How simplifying and flexible is the simplifying assumption in pair-copula constructions - analytic answers in dimension three and a glimpse beyond. (2021) https://doi.org/10.1214/21-EJS1832

[29] J. Fernández Sánchez, W. Trutschnig, M. Tschimpke: Markov product invariance in classes of bivariate copulas characterised by univariate functions. (2021) https://doi.org/10.1016/j.jmaa.2021.125184

[28] S. FoxF.M.L. Di Lascio and F. Durante: Dissimilarity functions for rank-based hierarchical clustering of continuous variables. (2021) https://doi.org/10.48550/arXiv.2007.04799

[27] F. CountC.D. Hofer, M. Niethammer, R. Kwitt: Dissecting Supervised Constrastive Learning. (2021) https://doi.org/10.48550/arXiv.2102.08817

[26] A. Kovács-GyőriB. Resch: Towards an automated spatial workflow for the global monitoring of public urban green accessibility in the light of the sustainable development goals. (2021) https://gispoint.de/index.php?eID=dumpFile&t=f&f=13767&token=3c9cbd4271a31ac59883f4e7c0f34fa4e3b80f5e&download=

[25] R.R. Junker, F. Griessenberger, W. Trutschnig: Estimating scale-invariant directed dependence of bivariate distributions. (2021) https://doi.org/10.1016/j.csda.2020.107058

[24] W. Senker, H. Stefanits, M. Gmeiner, W. TrutschnigC. Radl, A. Gruber: The Influence of Smoking in Minimally Invasive Spinal Fusion Surgery. (2021) https://doi.org/10.1515/med-2021-0223

2020

[23] S. Fox, W. Trutschnig: On quantile-based co-risk measures and their estimation. (2020) https://doi.org/10.1515/demo-2020-0021

[22] V. Cain, S. HirländerB. Goddard, F.M.Velotti, G. Zevi Della Porta, N. Bruchon, G. Valentino: Sample-efficient reinforcement learning for CERN accelerator control. (2020) https://doi.org/10.1103/PhysRevAccelBeams.23.124801

[21] A. Kovács-GyőriA. Ristea, C. Havas, M. Mehaffy, H.H. Hochmair, B. Resch, L. Juhasz, A. Lehner, L. Ramasubramanian, T. Blaschke: Opportunities and Challenges of Geospatial Analysis for Promoting Urban Livability in the Era of Big Data and Machine Learning. (2020) https://doi.org/10.3390/ijgi9120752

[20] F. Durante, J. Fernández Sánchez, W. TrutschnigM. Úbeda-Flores: On the size of subclasses of quasi-copulas and their Dedekind-MacNeille completion. (2020) https://doi.org/10.3390/math8122238

[19] T. Kiesslich, M. Beyreis, G. CarpenterA. Traweger: Citation inequality and the Journal Impact Factor: median, mean, (does it) matter? . (2020) https://doi.org/10.1007/s11192-020-03812-y

[18] G. Carpenter: To rank or to permute when comparing an ordinal outcome between two groups while adjusting for a covariate?. (2020) https://doi.org/10.1007/978-3-030-57306-5_48

[17] M. Leitinger, K.N. Poppert, M. Mauritz, F. Rossini, G. CarpenterA. Rohracher, G. Kalss, G. Kuchukhidze, J. Höfler, P. Bosque Varela, R. Kreidenhuber, K. Volna, C. Neuray, T. Kobulashvili, C.A. Granbichler, U. Siebert, E. Trinka: Status epilepticus admissions during the COVID-19 pandemic in Salzburg. A population-based study. (2020) https://doi.org/10.1111/epi.16737

[16] J. Fernández Sánchez, D.L. Rodríguez-Vidanes, J.B. Seoane-Sepúlveda, W. Trutschnig: Lineability, differentiable functions and special derivatives. (2020) https://doi.org/10.1007/s43037-020-00103-9

[15] J.Y. Ahn, S. Fox, R. Oh: A copula transformation in multivariate mixed discrete-continuous models. (2020) https://doi.org/10.1016/j.fss.2020.11.008

[14] F. Durante, J. Fernández Sánchez, C. Ignazzi, W. Trutschnig: On extremal problems for pairs of uniformly distributed sequences and integrals with respect to copula measures. (2020) https://doi.org/10.2478/udt-2020-0013

[13] M. Wagner, A. BathkeS.C. Cary, T.G.A. Green, R.R. Junker, W. Trutschnig, U. Ruprecht: Myco- and photobiont associations in crustose lichens in the McMurdo Dry Valleys (Antarctica) reveal high differentiation along an elevational gradient. (2020) https://doi.org/10.1007/s00300-020-02754-8

[12] S. FoxK.D. Schmidt: On order statistics and Kendall's tau for copulas. (2020) https://doi.org/10.1016/j.spl.2020.108972

[11] E. Brunner, F. Konietschke, A. BathkeM. Pauly: Ranks and Pseudo-ranks-Surprising Results of Certain Rank Tests in Unbalanced Designs. (2020) https://doi.org/10.1111/insr.12418

[10] A. Thomschewski, N. Gerner, P. Langthaler, A. Bathke, et al: Automatic vs. Manual Detection of High Frequency Oscillations in Intracranial Recordings From the Human Temporal Lobe. (2020) https://doi.org/10.3389/fneur.2020.563577

[9] L. Bernal-González, J. Fernández Sánchez, J.B. Seoane-Sepúlveda, W. Trutschnig: Highly tempering infinite matrices II: From divergence to convergence via Toeplitz-Silverman matrices. (2020) https://doi.org/10.1007/s13398-020-00934-z

[8] G. CarpenterE. Trinka: Accounting for individual variability in baseline seizure frequencies when planning randomised clinical trials remains challenging. (2020) https://doi.org/10.1111/epi.16676

[7] A. Egger-Rainer, E. Trinka, G. CarpenterS. Arnold, C. Boßelmann, H. Hamer, A. Hengsberger, J. Lang, H. Lerche, S. Noachtar, E. Pataraia, A. Schulze-Bonhage, A.M. Staack, I. Unterberger, S. Lorenzl: Assessing comfort in the epilepsy monitoring unit: Psychometric testing of an instrument. (2020) https://doi.org/10.1016/j.yebeh.2020.107460

[6] M.R. Berthold, C. BorgeltF. Höppner, F. Klawonn, R. Silipo: Guide to Intelligent Data Science (2nd edition). (2020) https://doi.org/10.1007/978-3-030-45574-3

[5] J. Fernández-Sánchez, D.L. Rodríguez-Vidanes, J.B. Seoane-Sepúlveda, W. Trutschnig: Lineability and integrability in the sense of Riemann, Lebesgue, Denjoy, and Khintchine. (2020) https://doi.org/10.1016/j.jmaa.2020.124433

[4] A.S. Berghoff, M. Gansterer, A. Bathke, W. TrutschnigP. Hungerländer, J.M.Berger, J. Kreminger, A.M. Starzer, R. Strassl, R. Schmid, H. Willschke, W. Lamm, M. Raderer, A.D. Gottlieb, N.J. Mauser, M. Preusser: SARS-CoV-2 Testing in Patients With Cancer Treated at a Tertiary Care Hospital During the COVID-19 Pandemic. (2020) https://ascopubs.org/doi/10.1200/JCO.20.01442

[3] F.X.Vialard, R. Kwitt, S. Wei, M. Niethammer: A Shooting Formulation of Deep Learning. (2020) https://doi.org/10.48550/arXiv.2006.10330

[2] S. HirländerN. Bruchon: Model-free and Bayesian Ensembling Model-based Deep Reinforcement Learning for Particle Accelerator Control Demonstrated on the FERMI FEL. (2020) https://doi.org/10.48550/arXiv.2006.10330

[1] C. Borgelt: Even Faster Exact k-Means Clustering. (2020) https://doi.org/10.1007/978-3-030-44584-3_8