Mathias Lechner

Graduate School
Henzinger_Thomas Group

31 Publications

Mark all

[31]
2023 | Conference Paper | IST-REx-ID: 13142 | OA
Chatterjee, Krishnendu, Thomas A Henzinger, Mathias Lechner, and Dorde Zikelic. “A Learner-Verifier Framework for Neural Network Controllers and Certificates of Stochastic Systems.” In Tools and Algorithms for the Construction and Analysis of Systems , 13993:3–25. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30823-9_1.
[Published Version] View | Files available | DOI
 
[30]
2023 | Journal Article | IST-REx-ID: 12704 | OA
Lechner, Mathias, Alexander Amini, Daniela Rus, and Thomas A Henzinger. “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” IEEE Robotics and Automation Letters. Institute of Electrical and Electronics Engineers, 2023. https://doi.org/10.1109/LRA.2023.3240930.
[Published Version] View | Files available | DOI | WoS | arXiv
 
[29]
2023 | Conference Paper | IST-REx-ID: 14242 | OA
Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, Thomas A Henzinger, and Daniela Rus. “Quantization-Aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks.” In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 37:14964–73. Association for the Advancement of Artificial Intelligence, 2023. https://doi.org/10.1609/aaai.v37i12.26747.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[28]
2023 | Conference Paper | IST-REx-ID: 14559
Ansaripour, Matin, Krishnendu Chatterjee, Thomas A Henzinger, Mathias Lechner, and Dorde Zikelic. “Learning Provably Stabilizing Neural Controllers for Discrete-Time Stochastic Systems.” In 21st International Symposium on Automated Technology for Verification and Analysis, 14215:357–79. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-45329-8_17.
View | DOI
 
[27]
2023 | Conference Paper | IST-REx-ID: 14830
Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee. “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.” In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 37:11926–35. Association for the Advancement of Artificial Intelligence, 2023. https://doi.org/10.1609/aaai.v37i10.26407.
[Preprint] View | Files available | DOI | arXiv
 
[26]
2023 | Conference Paper | IST-REx-ID: 15023 | OA
Zikelic, Dorde, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee, and Thomas A Henzinger. “Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees.” In 37th Conference on Neural Information Processing Systems, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[25]
2022 | Conference Paper | IST-REx-ID: 12010 | OA
Brunnbauer, Axel, Luigi Berducci, Andreas Brandstatter, Mathias Lechner, Ramin Hasani, Daniela Rus, and Radu Grosu. “Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing.” In 2022 International Conference on Robotics and Automation, 7513–20. IEEE, 2022. https://doi.org/10.1109/ICRA46639.2022.9811650.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[24]
2022 | Preprint | IST-REx-ID: 11366 | OA
Lechner, Mathias, Alexander Amini, Daniela Rus, and Thomas A Henzinger. “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2204.07373.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[23]
2022 | Journal Article | IST-REx-ID: 12147 | OA
Hasani, Ramin, Mathias Lechner, Alexander Amini, Lucas Liebenwein, Aaron Ray, Max Tschaikowski, Gerald Teschl, and Daniela Rus. “Closed-Form Continuous-Time Neural Networks.” Nature Machine Intelligence. Springer Nature, 2022. https://doi.org/10.1038/s42256-022-00556-7.
[Published Version] View | Files available | DOI | WoS | arXiv
 
[22]
2022 | Thesis | IST-REx-ID: 11362 | OA
Lechner, Mathias. “Learning Verifiable Representations.” Institute of Science and Technology Austria, 2022. https://doi.org/10.15479/at:ista:11362.
[Published Version] View | Files available | DOI
 
[21]
2022 | Journal Article | IST-REx-ID: 12510 | OA
Gruenbacher, Sophie A., Mathias Lechner, Ramin Hasani, Daniela Rus, Thomas A Henzinger, Scott A. Smolka, and Radu Grosu. “GoTube: Scalable Statistical Verification of Continuous-Depth Models.” Proceedings of the AAAI Conference on Artificial Intelligence. Association for the Advancement of Artificial Intelligence, 2022. https://doi.org/10.1609/aaai.v36i6.20631.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[20]
2022 | Journal Article | IST-REx-ID: 12511 | OA
Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, and Thomas A Henzinger. “Stability Verification in Stochastic Control Systems via Neural Network Supermartingales.” Proceedings of the AAAI Conference on Artificial Intelligence. Association for the Advancement of Artificial Intelligence, 2022. https://doi.org/10.1609/aaai.v36i7.20695.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[19]
2022 | Preprint | IST-REx-ID: 14601 | OA
Zikelic, Dorde, Mathias Lechner, Krishnendu Chatterjee, and Thomas A Henzinger. “Learning Stabilizing Policies in Stochastic Control Systems.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2205.11991.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[18]
2022 | Preprint | IST-REx-ID: 14600 | OA
Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee. “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.” ArXiv, n.d. https://doi.org/10.48550/ARXIV.2210.05308.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[17]
2021 | Conference Paper | IST-REx-ID: 10669 | OA
Grunbacher, Sophie, Ramin Hasani, Mathias Lechner, Jacek Cyranka, Scott A Smolka, and Radu Grosu. “On the Verification of Neural ODEs with Stochastic Guarantees.” In Proceedings of the AAAI Conference on Artificial Intelligence, 35:11525–35. AAAI Press, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[16]
2021 | Conference Paper | IST-REx-ID: 10671 | OA
Hasani, Ramin, Mathias Lechner, Alexander Amini, Daniela Rus, and Radu Grosu. “Liquid Time-Constant Networks.” In Proceedings of the AAAI Conference on Artificial Intelligence, 35:7657–66. AAAI Press, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[15]
2021 | Conference Paper | IST-REx-ID: 10668 | OA
Babaiee, Zahra, Ramin Hasani, Mathias Lechner, Daniela Rus, and Radu Grosu. “On-off Center-Surround Receptive Fields for Accurate and Robust Image Classification.” In Proceedings of the 38th International Conference on Machine Learning, 139:478–89. ML Research Press, 2021.
[Published Version] View | Files available | Download Published Version (ext.)
 
[14]
2021 | Conference Paper | IST-REx-ID: 10670 | OA
Vorbach, Charles J, Ramin Hasani, Alexander Amini, Mathias Lechner, and Daniela Rus. “Causal Navigation by Continuous-Time Neural Networks.” In 35th Conference on Neural Information Processing Systems, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[13]
2021 | Conference Paper | IST-REx-ID: 10665 | OA
Henzinger, Thomas A, Mathias Lechner, and Dorde Zikelic. “Scalable Verification of Quantized Neural Networks.” In Proceedings of the AAAI Conference on Artificial Intelligence, 35:3787–95. AAAI Press, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[12]
2021 | Conference Paper | IST-REx-ID: 10667 | OA
Lechner, Mathias, Ðorđe Žikelić, Krishnendu Chatterjee, and Thomas A Henzinger. “Infinite Time Horizon Safety of Bayesian Neural Networks.” In 35th Conference on Neural Information Processing Systems, 2021. https://doi.org/10.48550/arXiv.2111.03165.
[Published Version] View | Files available | DOI | Download Published Version (ext.) | arXiv
 
[11]
2021 | Journal Article | IST-REx-ID: 10404 | OA
Sietzen, Stefan, Mathias Lechner, Judy Borowski, Ramin Hasani, and Manuela Waldner. “Interactive Analysis of CNN Robustness.” Computer Graphics Forum. Wiley, 2021. https://doi.org/10.1111/cgf.14418.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
[10]
2021 | Conference Paper | IST-REx-ID: 10666 | OA
Lechner, Mathias, Ramin Hasani, Radu Grosu, Daniela Rus, and Thomas A Henzinger. “Adversarial Training Is Not Ready for Robot Learning.” In 2021 IEEE International Conference on Robotics and Automation, 4140–47. ICRA, 2021. https://doi.org/10.1109/ICRA48506.2021.9561036.
View | Files available | DOI | Download None (ext.) | WoS | arXiv
 
[9]
2020 | Conference Paper | IST-REx-ID: 10673 | OA
Hasani, Ramin, Mathias Lechner, Alexander Amini, Daniela Rus, and Radu Grosu. “A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits.” In Proceedings of the 37th International Conference on Machine Learning, 4082–93. PMLR, 2020.
[Published Version] View | Files available | Download Published Version (ext.)
 
[8]
2020 | Conference Paper | IST-REx-ID: 9103 | OA
Gruenbacher, Sophie, Jacek Cyranka, Mathias Lechner, Md Ariful Islam, Scott A. Smolka, and Radu Grosu. “Lagrangian Reachtubes: The next Generation.” In Proceedings of the 59th IEEE Conference on Decision and Control, 2020:1556–63. IEEE, 2020. https://doi.org/10.1109/CDC42340.2020.9304042.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[7]
2020 | Conference Paper | IST-REx-ID: 10672 | OA
Lechner, Mathias. “Learning Representations for Binary-Classification without Backpropagation.” In 8th International Conference on Learning Representations. ICLR, 2020.
[Published Version] View | Files available | Download Published Version (ext.)
 
[6]
2020 | Conference Paper | IST-REx-ID: 7808 | OA
Giacobbe, Mirco, Thomas A Henzinger, and Mathias Lechner. “How Many Bits Does It Take to Quantize Your Neural Network?” In International Conference on Tools and Algorithms for the Construction and Analysis of Systems, 12079:79–97. Springer Nature, 2020. https://doi.org/10.1007/978-3-030-45237-7_5.
[Published Version] View | Files available | DOI
 
[5]
2020 | Conference Paper | IST-REx-ID: 8194 | OA
Baranowski, Marek, Shaobo He, Mathias Lechner, Thanh Son Nguyen, and Zvonimir Rakamarić. “An SMT Theory of Fixed-Point Arithmetic.” In Automated Reasoning, 12166:13–31. Springer Nature, 2020. https://doi.org/10.1007/978-3-030-51074-9_2.
[Published Version] View | DOI | Download Published Version (ext.) | WoS
 
[4]
2020 | Journal Article | IST-REx-ID: 8679
Lechner, Mathias, Ramin Hasani, Alexander Amini, Thomas A Henzinger, Daniela Rus, and Radu Grosu. “Neural Circuit Policies Enabling Auditable Autonomy.” Nature Machine Intelligence. Springer Nature, 2020. https://doi.org/10.1038/s42256-020-00237-3.
View | Files available | DOI | WoS
 
[3]
2020 | Conference Paper | IST-REx-ID: 8704 | OA
Lechner, Mathias, Ramin Hasani, Daniela Rus, and Radu Grosu. “Gershgorin Loss Stabilizes the Recurrent Neural Network Compartment of an End-to-End Robot Learning Scheme.” In Proceedings - IEEE International Conference on Robotics and Automation, 5446–52. IEEE, 2020. https://doi.org/10.1109/ICRA40945.2020.9196608.
[Submitted Version] View | Files available | DOI | WoS
 
[2]
2019 | Conference Paper | IST-REx-ID: 6888 | OA
Lechner, Mathias, Ramin Hasani, Manuel Zimmer, Thomas A Henzinger, and Radu Grosu. “Designing Worm-Inspired Neural Networks for Interpretable Robotic Control.” In Proceedings - IEEE International Conference on Robotics and Automation, Vol. 2019–May. IEEE, 2019. https://doi.org/10.1109/icra.2019.8793840.
[Submitted Version] View | Files available | DOI
 
[1]
2019 | Conference Paper | IST-REx-ID: 6985 | OA
Hasani, Ramin, Alexander Amini, Mathias Lechner, Felix Naser, Radu Grosu, and Daniela Rus. “Response Characterization for Auditing Cell Dynamics in Long Short-Term Memory Networks.” In Proceedings of the International Joint Conference on Neural Networks. IEEE, 2019. https://doi.org/10.1109/ijcnn.2019.8851954.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
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31 Publications

Mark all

[31]
2023 | Conference Paper | IST-REx-ID: 13142 | OA
Chatterjee, Krishnendu, Thomas A Henzinger, Mathias Lechner, and Dorde Zikelic. “A Learner-Verifier Framework for Neural Network Controllers and Certificates of Stochastic Systems.” In Tools and Algorithms for the Construction and Analysis of Systems , 13993:3–25. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30823-9_1.
[Published Version] View | Files available | DOI
 
[30]
2023 | Journal Article | IST-REx-ID: 12704 | OA
Lechner, Mathias, Alexander Amini, Daniela Rus, and Thomas A Henzinger. “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” IEEE Robotics and Automation Letters. Institute of Electrical and Electronics Engineers, 2023. https://doi.org/10.1109/LRA.2023.3240930.
[Published Version] View | Files available | DOI | WoS | arXiv
 
[29]
2023 | Conference Paper | IST-REx-ID: 14242 | OA
Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, Thomas A Henzinger, and Daniela Rus. “Quantization-Aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks.” In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 37:14964–73. Association for the Advancement of Artificial Intelligence, 2023. https://doi.org/10.1609/aaai.v37i12.26747.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[28]
2023 | Conference Paper | IST-REx-ID: 14559
Ansaripour, Matin, Krishnendu Chatterjee, Thomas A Henzinger, Mathias Lechner, and Dorde Zikelic. “Learning Provably Stabilizing Neural Controllers for Discrete-Time Stochastic Systems.” In 21st International Symposium on Automated Technology for Verification and Analysis, 14215:357–79. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-45329-8_17.
View | DOI
 
[27]
2023 | Conference Paper | IST-REx-ID: 14830
Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee. “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.” In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 37:11926–35. Association for the Advancement of Artificial Intelligence, 2023. https://doi.org/10.1609/aaai.v37i10.26407.
[Preprint] View | Files available | DOI | arXiv
 
[26]
2023 | Conference Paper | IST-REx-ID: 15023 | OA
Zikelic, Dorde, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee, and Thomas A Henzinger. “Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees.” In 37th Conference on Neural Information Processing Systems, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[25]
2022 | Conference Paper | IST-REx-ID: 12010 | OA
Brunnbauer, Axel, Luigi Berducci, Andreas Brandstatter, Mathias Lechner, Ramin Hasani, Daniela Rus, and Radu Grosu. “Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing.” In 2022 International Conference on Robotics and Automation, 7513–20. IEEE, 2022. https://doi.org/10.1109/ICRA46639.2022.9811650.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[24]
2022 | Preprint | IST-REx-ID: 11366 | OA
Lechner, Mathias, Alexander Amini, Daniela Rus, and Thomas A Henzinger. “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2204.07373.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[23]
2022 | Journal Article | IST-REx-ID: 12147 | OA
Hasani, Ramin, Mathias Lechner, Alexander Amini, Lucas Liebenwein, Aaron Ray, Max Tschaikowski, Gerald Teschl, and Daniela Rus. “Closed-Form Continuous-Time Neural Networks.” Nature Machine Intelligence. Springer Nature, 2022. https://doi.org/10.1038/s42256-022-00556-7.
[Published Version] View | Files available | DOI | WoS | arXiv
 
[22]
2022 | Thesis | IST-REx-ID: 11362 | OA
Lechner, Mathias. “Learning Verifiable Representations.” Institute of Science and Technology Austria, 2022. https://doi.org/10.15479/at:ista:11362.
[Published Version] View | Files available | DOI
 
[21]
2022 | Journal Article | IST-REx-ID: 12510 | OA
Gruenbacher, Sophie A., Mathias Lechner, Ramin Hasani, Daniela Rus, Thomas A Henzinger, Scott A. Smolka, and Radu Grosu. “GoTube: Scalable Statistical Verification of Continuous-Depth Models.” Proceedings of the AAAI Conference on Artificial Intelligence. Association for the Advancement of Artificial Intelligence, 2022. https://doi.org/10.1609/aaai.v36i6.20631.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[20]
2022 | Journal Article | IST-REx-ID: 12511 | OA
Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, and Thomas A Henzinger. “Stability Verification in Stochastic Control Systems via Neural Network Supermartingales.” Proceedings of the AAAI Conference on Artificial Intelligence. Association for the Advancement of Artificial Intelligence, 2022. https://doi.org/10.1609/aaai.v36i7.20695.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[19]
2022 | Preprint | IST-REx-ID: 14601 | OA
Zikelic, Dorde, Mathias Lechner, Krishnendu Chatterjee, and Thomas A Henzinger. “Learning Stabilizing Policies in Stochastic Control Systems.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2205.11991.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[18]
2022 | Preprint | IST-REx-ID: 14600 | OA
Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee. “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.” ArXiv, n.d. https://doi.org/10.48550/ARXIV.2210.05308.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
[17]
2021 | Conference Paper | IST-REx-ID: 10669 | OA
Grunbacher, Sophie, Ramin Hasani, Mathias Lechner, Jacek Cyranka, Scott A Smolka, and Radu Grosu. “On the Verification of Neural ODEs with Stochastic Guarantees.” In Proceedings of the AAAI Conference on Artificial Intelligence, 35:11525–35. AAAI Press, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[16]
2021 | Conference Paper | IST-REx-ID: 10671 | OA
Hasani, Ramin, Mathias Lechner, Alexander Amini, Daniela Rus, and Radu Grosu. “Liquid Time-Constant Networks.” In Proceedings of the AAAI Conference on Artificial Intelligence, 35:7657–66. AAAI Press, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[15]
2021 | Conference Paper | IST-REx-ID: 10668 | OA
Babaiee, Zahra, Ramin Hasani, Mathias Lechner, Daniela Rus, and Radu Grosu. “On-off Center-Surround Receptive Fields for Accurate and Robust Image Classification.” In Proceedings of the 38th International Conference on Machine Learning, 139:478–89. ML Research Press, 2021.
[Published Version] View | Files available | Download Published Version (ext.)
 
[14]
2021 | Conference Paper | IST-REx-ID: 10670 | OA
Vorbach, Charles J, Ramin Hasani, Alexander Amini, Mathias Lechner, and Daniela Rus. “Causal Navigation by Continuous-Time Neural Networks.” In 35th Conference on Neural Information Processing Systems, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[13]
2021 | Conference Paper | IST-REx-ID: 10665 | OA
Henzinger, Thomas A, Mathias Lechner, and Dorde Zikelic. “Scalable Verification of Quantized Neural Networks.” In Proceedings of the AAAI Conference on Artificial Intelligence, 35:3787–95. AAAI Press, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[12]
2021 | Conference Paper | IST-REx-ID: 10667 | OA
Lechner, Mathias, Ðorđe Žikelić, Krishnendu Chatterjee, and Thomas A Henzinger. “Infinite Time Horizon Safety of Bayesian Neural Networks.” In 35th Conference on Neural Information Processing Systems, 2021. https://doi.org/10.48550/arXiv.2111.03165.
[Published Version] View | Files available | DOI | Download Published Version (ext.) | arXiv
 
[11]
2021 | Journal Article | IST-REx-ID: 10404 | OA
Sietzen, Stefan, Mathias Lechner, Judy Borowski, Ramin Hasani, and Manuela Waldner. “Interactive Analysis of CNN Robustness.” Computer Graphics Forum. Wiley, 2021. https://doi.org/10.1111/cgf.14418.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
[10]
2021 | Conference Paper | IST-REx-ID: 10666 | OA
Lechner, Mathias, Ramin Hasani, Radu Grosu, Daniela Rus, and Thomas A Henzinger. “Adversarial Training Is Not Ready for Robot Learning.” In 2021 IEEE International Conference on Robotics and Automation, 4140–47. ICRA, 2021. https://doi.org/10.1109/ICRA48506.2021.9561036.
View | Files available | DOI | Download None (ext.) | WoS | arXiv
 
[9]
2020 | Conference Paper | IST-REx-ID: 10673 | OA
Hasani, Ramin, Mathias Lechner, Alexander Amini, Daniela Rus, and Radu Grosu. “A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits.” In Proceedings of the 37th International Conference on Machine Learning, 4082–93. PMLR, 2020.
[Published Version] View | Files available | Download Published Version (ext.)
 
[8]
2020 | Conference Paper | IST-REx-ID: 9103 | OA
Gruenbacher, Sophie, Jacek Cyranka, Mathias Lechner, Md Ariful Islam, Scott A. Smolka, and Radu Grosu. “Lagrangian Reachtubes: The next Generation.” In Proceedings of the 59th IEEE Conference on Decision and Control, 2020:1556–63. IEEE, 2020. https://doi.org/10.1109/CDC42340.2020.9304042.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[7]
2020 | Conference Paper | IST-REx-ID: 10672 | OA
Lechner, Mathias. “Learning Representations for Binary-Classification without Backpropagation.” In 8th International Conference on Learning Representations. ICLR, 2020.
[Published Version] View | Files available | Download Published Version (ext.)
 
[6]
2020 | Conference Paper | IST-REx-ID: 7808 | OA
Giacobbe, Mirco, Thomas A Henzinger, and Mathias Lechner. “How Many Bits Does It Take to Quantize Your Neural Network?” In International Conference on Tools and Algorithms for the Construction and Analysis of Systems, 12079:79–97. Springer Nature, 2020. https://doi.org/10.1007/978-3-030-45237-7_5.
[Published Version] View | Files available | DOI
 
[5]
2020 | Conference Paper | IST-REx-ID: 8194 | OA
Baranowski, Marek, Shaobo He, Mathias Lechner, Thanh Son Nguyen, and Zvonimir Rakamarić. “An SMT Theory of Fixed-Point Arithmetic.” In Automated Reasoning, 12166:13–31. Springer Nature, 2020. https://doi.org/10.1007/978-3-030-51074-9_2.
[Published Version] View | DOI | Download Published Version (ext.) | WoS
 
[4]
2020 | Journal Article | IST-REx-ID: 8679
Lechner, Mathias, Ramin Hasani, Alexander Amini, Thomas A Henzinger, Daniela Rus, and Radu Grosu. “Neural Circuit Policies Enabling Auditable Autonomy.” Nature Machine Intelligence. Springer Nature, 2020. https://doi.org/10.1038/s42256-020-00237-3.
View | Files available | DOI | WoS
 
[3]
2020 | Conference Paper | IST-REx-ID: 8704 | OA
Lechner, Mathias, Ramin Hasani, Daniela Rus, and Radu Grosu. “Gershgorin Loss Stabilizes the Recurrent Neural Network Compartment of an End-to-End Robot Learning Scheme.” In Proceedings - IEEE International Conference on Robotics and Automation, 5446–52. IEEE, 2020. https://doi.org/10.1109/ICRA40945.2020.9196608.
[Submitted Version] View | Files available | DOI | WoS
 
[2]
2019 | Conference Paper | IST-REx-ID: 6888 | OA
Lechner, Mathias, Ramin Hasani, Manuel Zimmer, Thomas A Henzinger, and Radu Grosu. “Designing Worm-Inspired Neural Networks for Interpretable Robotic Control.” In Proceedings - IEEE International Conference on Robotics and Automation, Vol. 2019–May. IEEE, 2019. https://doi.org/10.1109/icra.2019.8793840.
[Submitted Version] View | Files available | DOI
 
[1]
2019 | Conference Paper | IST-REx-ID: 6985 | OA
Hasani, Ramin, Alexander Amini, Mathias Lechner, Felix Naser, Radu Grosu, and Daniela Rus. “Response Characterization for Auditing Cell Dynamics in Long Short-Term Memory Networks.” In Proceedings of the International Joint Conference on Neural Networks. IEEE, 2019. https://doi.org/10.1109/ijcnn.2019.8851954.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
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