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5 Publications
2024 | Published | Conference Paper | IST-REx-ID: 17898
Overparametrization helps offline-to-online generalization of closed-loop control from pixels
Lechner, Mathias, Overparametrization helps offline-to-online generalization of closed-loop control from pixels. Proceedings of the 2024 IEEE International Conference on Robotics and Automation. 2024
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Lechner, Mathias, Overparametrization helps offline-to-online generalization of closed-loop control from pixels. Proceedings of the 2024 IEEE International Conference on Robotics and Automation. 2024
2023 | Published | Conference Paper | IST-REx-ID: 12976 | 
Learning deposition policies for fused multi-material 3D printing
K. Liao, T. Tricard, M. Piovarci, H.-P. Seidel, V. Babaei, in:, 2023 IEEE International Conference on Robotics and Automation, IEEE, 2023, pp. 12345–12352.
[Submitted Version]
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K. Liao, T. Tricard, M. Piovarci, H.-P. Seidel, V. Babaei, in:, 2023 IEEE International Conference on Robotics and Automation, IEEE, 2023, pp. 12345–12352.
2022 | Published | Conference Paper | IST-REx-ID: 12010 |
Latent imagination facilitates zero-shot transfer in autonomous racing
A. Brunnbauer, L. Berducci, A. Brandstatter, M. Lechner, R. Hasani, D. Rus, R. Grosu, in:, 2022 International Conference on Robotics and Automation, IEEE, 2022, pp. 7513–7520.
[Preprint]
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A. Brunnbauer, L. Berducci, A. Brandstatter, M. Lechner, R. Hasani, D. Rus, R. Grosu, in:, 2022 International Conference on Robotics and Automation, IEEE, 2022, pp. 7513–7520.
2021 | Published | Conference Paper | IST-REx-ID: 10666 |
Adversarial training is not ready for robot learning
Lechner, Mathias, Adversarial training is not ready for robot learning. 2021 IEEE International Conference on Robotics and Automation. 2021
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| arXiv
Lechner, Mathias, Adversarial training is not ready for robot learning. 2021 IEEE International Conference on Robotics and Automation. 2021
2020 | Published | Conference Paper | IST-REx-ID: 8704 |
Gershgorin loss stabilizes the recurrent neural network compartment of an end-to-end robot learning scheme
Lechner, Mathias, Gershgorin loss stabilizes the recurrent neural network compartment of an end-to-end robot learning scheme. Proceedings - IEEE International Conference on Robotics and Automation. 2020
[Submitted Version]
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Lechner, Mathias, Gershgorin loss stabilizes the recurrent neural network compartment of an end-to-end robot learning scheme. Proceedings - IEEE International Conference on Robotics and Automation. 2020