Understanding the Effects of Dataset Characteristics on Offline Reinforcement Learning. - Kajetan Schweighofer; Markus Hofmarcher; Marius-Constantin Dinu; Philipp Renz; Angela Bitto-Nemling; Vihang Patil; Sepp Hochreiter (CoRR, 2021)

A Dataset Perspective on Offline Reinforcement Learning. - Kajetan Schweighofer; Marius-Constantin Dinu; Andreas Radler; Markus Hofmarcher; Vihang Prakash Patil; Angela Bitto-Nemling; Hamid Eghbal-zadeh; Sepp Hochreiter (CoLLAs, 2022)

Quantification of Uncertainty with Adversarial Models. - Kajetan Schweighofer; Lukas Aichberger; Mykyta Ielanskyi; Günter Klambauer; Sepp Hochreiter (NeurIPS, 2023)

Introducing an Improved Information-Theoretic Measure of Predictive Uncertainty. - Kajetan Schweighofer; Lukas Aichberger; Mykyta Ielanskyi; Sepp Hochreiter (CoRR, 2023)

Semantically Diverse Language Generation for Uncertainty Estimation in Language Models. - Lukas Aichberger; Kajetan Schweighofer; Mykyta Ielanskyi; Sepp Hochreiter (CoRR, 2024)

The Disparate Benefits of Deep Ensembles. - Kajetan Schweighofer; Adrián Arnaiz-Rodríguez; Sepp Hochreiter; Nuria Oliver (CoRR, 2024)

Rethinking Uncertainty Estimation in Natural Language Generation. - Lukas Aichberger; Kajetan Schweighofer; Sepp Hochreiter (CoRR, 2024)

Improving Uncertainty Estimation through Semantically Diverse Language Generation. - Lukas Aichberger; Kajetan Schweighofer; Mykyta Ielanskyi; Sepp Hochreiter (ICLR, 2025)

On Information-Theoretic Measures of Predictive Uncertainty. - Kajetan Schweighofer; Lukas Aichberger; Mykyta Ielanskyi; Sepp Hochreiter (UAI, 2025)

ImageSet2Text: Describing Sets of Images through Text. - Piera Riccio; Francesco Galati; Kajetan Schweighofer; Noa Garcia; Nuria Oliver (CoRR, 2025)