Kajetan Schweighofer

19 papers A* 4A 1Journal 13Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	ImageSet2Text: Describing Sets of Images Through Text. AAAI Piera Riccio, Francesco Galati, Kajetan Schweighofer, Noa Garcia, Nuria Oliver
2025	J	`jnl`	Addressing Pitfalls in the Evaluation of Uncertainty Estimation Methods for Natural Language Generation. CoRR Mykyta Ielanskyi, Kajetan Schweighofer, Lukas Aichberger, Sepp Hochreiter
2025	J	`jnl`	Combining Bayesian and Evidential Uncertainty Quantification for Improved Bioactivity Modeling. J. Chem. Inf. Model. Bola Khalil, Kajetan Schweighofer, Natalia Dyubankova, Gerard J. P. van Westen, Herman van Vlijmen
2025	J	`jnl`	ImageSet2Text: Describing Sets of Images through Text. CoRR Piera Riccio, Francesco Galati, Kajetan Schweighofer, Noa Garcia, Nuria Oliver
2025	A*	`conf`	Improving Uncertainty Estimation through Semantically Diverse Language Generation. ICLR Lukas Aichberger, Kajetan Schweighofer, Mykyta Ielanskyi, Sepp Hochreiter
2025	A	`conf`	On Information-Theoretic Measures of Predictive Uncertainty. UAI Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Sepp Hochreiter
2025	J	`jnl`	Safe and Certifiable AI Systems: Concepts, Challenges, and Lessons Learned. CoRR Kajetan Schweighofer, Barbara Brune, Lukas Gruber, Simon Schmid, Alexander Aufreiter, Andreas Gruber, Thomas Doms, Sebastian Eder, Florian Mayer, Xaver-Paul Stadlbauer, Christoph Schwald, Werner Zellinger, Bernhard Nessler, Sepp Hochreiter
2025	A*	`conf`	The Disparate Benefits of Deep Ensembles. ICML Kajetan Schweighofer, Adrián Arnaiz-Rodríguez, Sepp Hochreiter, Nuria Oliver
2025	J	`jnl`	Uncertainty Quantification for Regression using Proper Scoring Rules. CoRR Alexander Fishkov, Kajetan Schweighofer, Mykyta Ielanskyi, Nikita Kotelevskii, Mohsen Guizani, Maxim Panov
2025	J	`jnl`	xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity. CoRR Maximilian Beck, Kajetan Schweighofer, Sebastian Böck, Sebastian Lehner, Sepp Hochreiter
2024	J	`jnl`	On Information-Theoretic Measures of Predictive Uncertainty. CoRR Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Sepp Hochreiter
2024	J	`jnl`	Rethinking Uncertainty Estimation in Natural Language Generation. CoRR Lukas Aichberger, Kajetan Schweighofer, Sepp Hochreiter
2024	J	`jnl`	Semantically Diverse Language Generation for Uncertainty Estimation in Language Models. CoRR Lukas Aichberger, Kajetan Schweighofer, Mykyta Ielanskyi, Sepp Hochreiter
2024	J	`jnl`	The Disparate Benefits of Deep Ensembles. CoRR Kajetan Schweighofer, Adrián Arnaiz-Rodríguez, Sepp Hochreiter, Nuria Oliver
2023	J	`jnl`	Introducing an Improved Information-Theoretic Measure of Predictive Uncertainty. CoRR Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Sepp Hochreiter
2023	A*	`conf`	Quantification of Uncertainty with Adversarial Models. NeurIPS Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Günter Klambauer, Sepp Hochreiter
2023	J	`jnl`	Quantification of Uncertainty with Adversarial Models. CoRR Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Günter Klambauer, Sepp Hochreiter
2022	—	`conf`	A Dataset Perspective on Offline Reinforcement Learning. CoLLAs Kajetan Schweighofer, Marius-Constantin Dinu, Andreas Radler, Markus Hofmarcher, Vihang Prakash Patil, Angela Bitto-Nemling, Hamid Eghbal-zadeh, Sepp Hochreiter
2021	J	`jnl`	Understanding the Effects of Dataset Characteristics on Offline Reinforcement Learning. CoRR Kajetan Schweighofer, Markus Hofmarcher, Marius-Constantin Dinu, Philipp Renz, Angela Bitto-Nemling, Vihang Patil, Sepp Hochreiter