| 2024 | DX | Inferring Sensor Placement Using Critical Pairs and Satisfiability Modulo Theory. | Alexander Diedrich, Ren Heesch, Marco Bozzano, Bjrn Ludwig, Alessandro Cimatti, Oliver Niggemann |
| 2024 | DX | Summary of "A Lazy Approach to Neural Numerical Planning with Control Parameters" (Extended Abstract). | Ren Heesch, Alessandro Cimatti, Jonas Ehrhardt, Alexander Diedrich, Oliver Niggemann |
| 2024 | DX | Design Principles for Falsifiable, Replicable and Reproducible Empirical Machine Learning Research. | Daniel Vranjes, Jonas Ehrhardt, Ren Heesch, Lukas Moddemann, Henrik Sebastian Steude, Oliver Niggemann |
| 2024 | ECAI | A Lazy Approach to Neural Numerical Planning with Control Parameters. | Ren Heesch, Alessandro Cimatti, Jonas Ehrhardt, Alexander Diedrich, Oliver Niggemann |
| 2023 | ECAI | Learning Process Steps as Dynamical Systems for a Sub-Symbolic Approach of Process Planning in Cyber-Physical Production Systems. | Jonas Ehrhardt, Ren Heesch, Oliver Niggemann |
| 2023 | ECAI | Integrating Machine Learning into an SMT-Based Planning Approach for Production Planning in Cyber-Physical Production Systems. | Ren Heesch, Jonas Ehrhardt, Oliver Niggemann |
| 2022 | ETFA | An AI benchmark for Diagnosis, Reconfiguration & Planning. | Jonas Ehrhardt, Malte Ramonat, Ren Heesch, Kaja Balzereit, Alexander Diedrich, Oliver Niggemann |