Kajetan Schweighofer
Scholar

Kajetan Schweighofer

Google Scholar ID: 9KMoqxEAAAAJ
PhD Student, Johannes Kepler University Linz
Machine LearningDeep LearningRobustnessUncertainty EstimationBayesian Deep Learning
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Citations & Impact
All-time
Citations
183
 
H-index
6
 
i10-index
5
 
Publications
17
 
Co-authors
16
list available
Contact
No contact links provided.
Publications
8 items
Addressing Pitfalls in the Evaluation of Uncertainty Estimation Methods for Natural Language Generation
2025
Cited
0
xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity
2025
Cited
0
Uncertainty Quantification for Regression using Proper Scoring Rules
2025
Cited
0
Safe and Certifiable AI Systems: Concepts, Challenges, and Lessons Learned
2025
Cited
0
ImageSet2Text: Describing Sets of Images through Text
2025
Cited
0
The Disparate Benefits of Deep Ensembles
arXiv.org · 2024
Cited
1
On Information-Theoretic Measures of Predictive Uncertainty
arXiv.org · 2024
Cited
3
Semantically Diverse Language Generation for Uncertainty Estimation in Language Models
arXiv.org · 2024
Cited
18
Resume (English only)
Co-authors
16 total
Sepp Hochreiter
Sepp Hochreiter
Institute for Machine Learning, Johannes Kepler University Linz
Lukas Aichberger
Lukas Aichberger
PhD Student, Johannes Kepler University Linz
Mykyta Ielanskyi
Mykyta Ielanskyi
PhD student ELLIS unit Linz
Co-author 4
Co-author 4
Marius-Constantin Dinu
Marius-Constantin Dinu
PhD, Institute of Machine Learning, JKU, Linz, ExtensityAI Research Scientist
Co-author 6
Co-author 6
Andreas Radler
Andreas Radler
PhD Student, Johannes Kepler University Linz
Günter Klambauer
Günter Klambauer
Prof., LIT AI Lab & Institute for Machine Learning, Johannes Kepler University