Enhanced Symbolic Regression Through Local Variable Transformations. - Jirí Kubalík; Erik Derner; Robert Babuska (IJCCI, 2017)

Data-driven Construction of Symbolic Process Models for Reinforcement Learning. - Erik Derner; Jirí Kubalík; Robert Babuska (ICRA, 2018)

Reinforcement Learning with Symbolic Input-Output Models. - Erik Derner; Jirí Kubalík; Robert Babuska (IROS, 2018)

Towards Life-Long Autonomy of Mobile Robots Through Feature-Based Change Detection. - Erik Derner; Clara Gómez; Alejandra C. Hernández; Ramón Barber; Robert Babuska (ECMR, 2019)

Semantic Localization through Propagation of Scene Information in a Hierarchical Model. - Clara Gómez; Alejandra C. Hernández; Erik Derner; Ramón Barber (ECMR, 2019)

Indoor Scene Recognition based on Weighted Voting Schemes. - Alejandra C. Hernández; Clara Gómez; Erik Derner; Ramón Barber (ECMR, 2019)

Vision-based Navigation Using Deep Reinforcement Learning. - Jonas Kulhanek; Erik Derner; Tim de Bruin; Robert Babuska (ECMR, 2019)

Symbolic Regression for Constructing Analytic Models in Reinforcement Learning. - Erik Derner; Jirí Kubalík; Nicola Ancona; Robert Babuska (CoRR, 2019)

Symbolic regression driven by training data and prior knowledge. - Jirí Kubalík; Erik Derner; Robert Babuska (GECCO, 2020)

Efficient Object Search Through Probability-Based Viewpoint Selection. - Alejandra C. Hernández; Erik Derner; Clara Gómez; Ramón Barber; Robert Babuska (IROS, 2020)

Constructing parsimonious analytic models for dynamic systems via symbolic regression. - Erik Derner; Jirí Kubalík; Nicola Ancona; Robert Babuska (Appl. Soft Comput., 2020)

Object-Based Pose Graph for Dynamic Indoor Environments. - Clara Gómez; Alejandra C. Hernández; Erik Derner; Ramón Barber; Robert Babuska (IEEE Robotics Autom. Lett., 2020)

Guiding Robot Model Construction with Prior Features. - Erik Derner; Jirí Kubalík; Robert Babuska (IROS, 2021)

Selecting Informative Data Samples for Model Learning Through Symbolic Regression. - Erik Derner; Jirí Kubalík; Robert Babuska (IEEE Access, 2021)

Symbolic Regression Methods for Reinforcement Learning. - Jirí Kubalík; Erik Derner; Jan Zegklitz; Robert Babuska (IEEE Access, 2021)

Multi-objective symbolic regression for physics-aware dynamic modeling. - Jirí Kubalík; Erik Derner; Robert Babuska (Expert Syst. Appl., 2021)

Visual Navigation in Real-World Indoor Environments Using End-to-End Deep Reinforcement Learning. - Jonas Kulhanek; Erik Derner; Robert Babuska (IEEE Robotics Autom. Lett., 2021)

Change detection using weighted features for image-based localization. - Erik Derner; Clara Gómez; Alejandra C. Hernández; Ramón Barber; Robert Babuska (Robotics Auton. Syst., 2021)

ViewFormer: NeRF-Free Neural Rendering from Few Images Using Transformers. - Jonas Kulhanek; Erik Derner; Torsten Sattler; Robert Babuska (ECCV (15), 2022)

Toward Physically Plausible Data-Driven Models: A Novel Neural Network Approach to Symbolic Regression. - Jirí Kubalík; Erik Derner; Robert Babuska (IEEE Access, 2023)

Neural Networks for Symbolic Regression. - Jirí Kubalík; Erik Derner; Robert Babuska (CoRR, 2023)

Beyond the Safeguards: Exploring the Security Risks of ChatGPT. - Erik Derner; Kristina Batistic (CoRR, 2023)

A Security Risk Taxonomy for Large Language Models. - Erik Derner; Kristina Batistic; Jan Zahálka; Robert Babuska (CoRR, 2023)

Can ChatGPT Read Who You Are? - Erik Derner; Dalibor Kucera; Nuria Oliver; Jan Zahálka (CoRR, 2023)

A Security Risk Taxonomy for Prompt-Based Interaction With Large Language Models. - Erik Derner; Kristina Batistic; Jan Zahálka; Robert Babuska (IEEE Access, 2024)

SymFormer: End-to-End Symbolic Regression Using Transformer-Based Architecture. - Martin Vastl; Jonas Kulhanek; Jirí Kubalík; Erik Derner; Robert Babuska (IEEE Access, 2024)

Leveraging Large Language Models to Measure Gender Bias in Gendered Languages. - Erik Derner; Sara Sansalvador de la Fuente; Yoan Gutiérrez; Paloma Moreda; Nuria Oliver (CoRR, 2024)