Mathias Lechner
Graduate School
Henzinger Group
6 Publications
2020 | Conference Paper | IST-REx-ID: 7808 |

Giacobbe, Mirco, et al. “How Many Bits Does It Take to Quantize Your Neural Network?” International Conference on Tools and Algorithms for the Construction and Analysis of Systems, vol. 12079, Springer Nature, 2020, pp. 79–97, doi:10.1007/978-3-030-45237-7_5.
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2020 | Conference Paper | IST-REx-ID: 8194 |

Baranowski, Marek, et al. “An SMT Theory of Fixed-Point Arithmetic.” Automated Reasoning, vol. 12166, Springer Nature, 2020, pp. 13–31, doi:10.1007/978-3-030-51074-9_2.
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| DOI
| Download Published Version (ext.)
2020 | Conference Paper | IST-REx-ID: 8704 |

Lechner, Mathias, et al. “Gershgorin Loss Stabilizes the Recurrent Neural Network Compartment of an End-to-End Robot Learning Scheme.” Proceedings - IEEE International Conference on Robotics and Automation, IEEE, 2020, pp. 5446–52, doi:10.1109/ICRA40945.2020.9196608.
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2020 | Journal Article | IST-REx-ID: 8679
Lechner, Mathias, et al. “Neural Circuit Policies Enabling Auditable Autonomy.” Nature Machine Intelligence, vol. 2, Springer Nature, 2020, pp. 642–52, doi:10.1038/s42256-020-00237-3.
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2019 | Conference Paper | IST-REx-ID: 6888 |

Lechner, Mathias, et al. “Designing Worm-Inspired Neural Networks for Interpretable Robotic Control.” Proceedings - IEEE International Conference on Robotics and Automation, vol. 2019–May, 8793840, IEEE, 2019, doi:10.1109/icra.2019.8793840.
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| DOI
2019 | Conference Paper | IST-REx-ID: 6985 |

Hasani, Ramin, et al. “Response Characterization for Auditing Cell Dynamics in Long Short-Term Memory Networks.” Proceedings of the International Joint Conference on Neural Networks, 8851954, IEEE, 2019, doi:10.1109/ijcnn.2019.8851954.
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| DOI
| Download Preprint (ext.)
| arXiv
6 Publications
2020 | Conference Paper | IST-REx-ID: 7808 |

Giacobbe, Mirco, et al. “How Many Bits Does It Take to Quantize Your Neural Network?” International Conference on Tools and Algorithms for the Construction and Analysis of Systems, vol. 12079, Springer Nature, 2020, pp. 79–97, doi:10.1007/978-3-030-45237-7_5.
View
| Files available
| DOI
2020 | Conference Paper | IST-REx-ID: 8194 |

Baranowski, Marek, et al. “An SMT Theory of Fixed-Point Arithmetic.” Automated Reasoning, vol. 12166, Springer Nature, 2020, pp. 13–31, doi:10.1007/978-3-030-51074-9_2.
View
| DOI
| Download Published Version (ext.)
2020 | Conference Paper | IST-REx-ID: 8704 |

Lechner, Mathias, et al. “Gershgorin Loss Stabilizes the Recurrent Neural Network Compartment of an End-to-End Robot Learning Scheme.” Proceedings - IEEE International Conference on Robotics and Automation, IEEE, 2020, pp. 5446–52, doi:10.1109/ICRA40945.2020.9196608.
View
| Files available
| DOI
2020 | Journal Article | IST-REx-ID: 8679
Lechner, Mathias, et al. “Neural Circuit Policies Enabling Auditable Autonomy.” Nature Machine Intelligence, vol. 2, Springer Nature, 2020, pp. 642–52, doi:10.1038/s42256-020-00237-3.
View
| Files available
| DOI
2019 | Conference Paper | IST-REx-ID: 6888 |

Lechner, Mathias, et al. “Designing Worm-Inspired Neural Networks for Interpretable Robotic Control.” Proceedings - IEEE International Conference on Robotics and Automation, vol. 2019–May, 8793840, IEEE, 2019, doi:10.1109/icra.2019.8793840.
View
| Files available
| DOI
2019 | Conference Paper | IST-REx-ID: 6985 |

Hasani, Ramin, et al. “Response Characterization for Auditing Cell Dynamics in Long Short-Term Memory Networks.” Proceedings of the International Joint Conference on Neural Networks, 8851954, IEEE, 2019, doi:10.1109/ijcnn.2019.8851954.
View
| DOI
| Download Preprint (ext.)
| arXiv