| Enhancing lattice-based motion planning with introspective learning and reasoning M Tiger, D Bergström, A Norrstig, F Heintz IEEE Robotics and Automation Letters 6 (3), 4385-4392, 2021 | 3 | 2021 |
| Bayesian optimization for selecting training and validation data for supervised machine learning D Bergström, M Tiger, F Heintz 31st Swedish AI Society Workshop (SAIS), 2019 | 1 | 2019 |
| Bt-GAN: Generating Fair Synthetic Healthdata via Bias-transforming Generative Adversarial Networks R Ramachandranpillai, F Sikder, D Bergström, F Heintz Authorea Preprints, 2023 | | 2023 |
| On-Demand Multi-Agent Basket Picking for Shopping Stores M Tiger, D Bergström, SW Stranius, E Holmgren, D de Leng, F Heintz 2023 IEEE International Conference on Robotics and Automation (ICRA), 5793-5799, 2023 | | 2023 |
| Learning Heuristics for Combinatorial Assignment by Optimally Solving Subproblems F Präntare, H Appelgren, M Tiger, D Bergström, F Heintz Proceedings of the 21st International Conference on Autonomous Agents and …, 2022 | | 2022 |
| Towards Utilitarian Combinatorial Assignment with Deep Neural Networks and Heuristic Algorithms F Präntare, M Tiger, D Bergström, H Appelgren, F Heintz International Workshop on the Foundations of Trustworthy AI Integrating …, 2020 | | 2020 |
| Bayesian optimization for selecting training and validation data for supervised machine learning: using Gaussian processes both to learn the relationship between sets of … D Bergström | | 2019 |
| Utveckling av en applikation för framtagning av hjärnresponser vid funktionell magnetresonanstomografi C Arvidsson, D Bergström, P Eilert, H Gudmundsson, C Henriksson, ... | | 2016 |
| Privacy-Preserving Synthetic Trajectory Data Generation D Bergström, MF Sikder, F Heintz | | |
Fredrik HeintzProfessor of Computer Science, Linköping UniversityEmail confirmado em liu.se
