My Research
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My research goal is to build deep neural networks that we can trust. Specifically, my research includes the topics
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List of Publications
* denotes equal contributions
2023
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Liquid Structural State-Space Models
Ramin Hasani*, Mathias Lechner*, Tsun-Hsuan Wang, Makram Chahine, Alexander Amini, Daniela Rus Accepted at the International Conference on Learning Representations (ICLR) , 2023 |
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Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning
Mathias Lechner, Alexander Amini, Daniela Rus, Thomas A. Henzinger Accepted at the IEEE Robotics and Automation Letters (RA-L) , 2023 |
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Quantization-aware Interval Bound Propagation for Training Certifiably Robust
Quantized Neural Networks
Mathias Lechner, Đorđe Žikelić, Krishnendu Chatterjee, Thomas A. Henzinger, Daniela Rus Accepted at the AAAI Conference on Artificial Intelligence (AAAI) , 2023 |
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Learning Control Policies for Stochastic Systems with Reach-avoid Guarantees
Đorđe Žikelić*, Mathias Lechner*, Thomas A. Henzinger, Krishnendu Chatterjee Accepted at the AAAI Conference on Artificial Intelligence (AAAI) , 2023 |
2022
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Closed-form continuous-time neural networks
Ramin Hasani*, Mathias Lechner*, Alexander Amini, Lucas Liebenwein, Aaron Ray, Max Tschaikowski, Gerald Teschl, Daniela Rus Nature Machine Intelligence, 2022 |
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PyHopper-A Plug-and-Play Hyperparameter Optimization Engine
Mathias Lechner, Ramin Hasani, Sophie Neubauer, Philipp Neubauer, Daniela Rus Has it Trained Yet? NeurIPS 2022 Workshop, 2022 |
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Are All Vision Models Created Equal? A Study of the Open-Loop to Closed-Loop Causality Gap
Mathias Lechner, Ramin Hasani, Alexander Amini, Tsun-Hsuan Wang, Thomas A Henzinger, Daniela Rus NeurIPS 2022 Machine Learning for Autonomous Driving Workshop (ML4AD), 2022 |
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Mixed-Memory RNNs for Learning Long-term Dependencies in Irregularly-sampled Time Series
Mathias Lechner, Ramin Hasani Memory in Artificial and Real Intelligence (MemARI) NeurIPS 2022 Workshop, 2022 |
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Infrastructure-based End-to-End Learning and Prevention of Driver Failure
Noam Buckman, Shiva Sreeram, Mathias Lechner, Yutong Ban, Ramin Hasani, Sertac Karaman, Daniela Rus 5th Robot Learning Workshop at NeurIPS: Trustworthy Robotics, 2022 |
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Learning Verifiable Representations
Mathias Lechner PhD thesis, 2022 |
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Learning Stabilizing Policies in Stochastic Control Systems
Đorđe Žikelić*, Mathias Lechner*, Krishnendu Chatterjee, Thomas A. Henzinger Workshop on Socially Responsible Machine Learning (SRML) at ICLR 2022, 2022 |
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Stability Verification in Stochastic Control Systems via Neural
Network
Supermartingales
Mathias Lechner*, Đorđe Žikelić*, Krishnendu Chatterjee, Thomas A. Henzinger AAAI Conference on Artificial Intelligence (AAAI) , 2022 |
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GoTube: Scalable Stochastic
Verification of
Continuous-Depth Models
Sophie Gruenbacher, Mathias Lechner, Ramin Hasani, Daniela Rus, Thomas A. Henzinger, Scott A. Smolka, Radu Grosu AAAI Conference on Artificial Intelligence (AAAI) , 2022 |
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Model-based versus Model-free Deep Reinforcement Learning for
Autonomous Racing Cars
Axel Brunnbauer*, Luigi Berducci*, Andreas Brandstätter*, Mathias Lechner, Ramin Hasani, Daniela Rus, Radu Grosu IEEE International Conference on Robotics and Automation (ICRA), 2022 |
2021
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Infinite
Time Horizon Safety of Bayesian Neural Networks
Mathias Lechner*, Đorđe Žikelić*, Krishnendu Chatterjee, Thomas A. Henzinger Conference on Neural Information Processing Systems (NeurIPS), 2021 |
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Causal
Navigation by Continuous-time Neural Networks
Charles J Vorbach*, Ramin Hasani*, Alexander Amini, Mathias Lechner, Daniela Rus Conference on Neural Information Processing Systems (NeurIPS), 2021 |
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On-Off Center-Surround
Receptive
Fields for Accurate and Robust Image
Zahra Babaiee, Ramin Hasani, Mathias Lechner, Daniela Rus, Radu Grosu International Conference on Machine Learning (ICML), 2021 |
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Adversarial Training is Not
Ready for Robot Learning
Mathias Lechner, Ramin Hasani, Radu Grosu, Daniela Rus, Thomas A. Henzinger IEEE International Conference on Robotics and Automation (ICRA), 2021 |
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Scalable Verification of
Quantized Neural Networks
Thomas A. Henzinger*, Mathias Lechner*, and Djordje Zikelic* (alphabetical) AAAI Conference on Artificial Intelligence (AAAI) , 2021 |
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Liquid Time-constant
Networks
Ramin Hasani*, Mathias Lechner*, Alexander Amini, Daniela Rus, and Radu Grosu AAAI Conference on Artificial Intelligence (AAAI) , 2021 |
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On
the Verification of Neural
ODEs with Stochastic
Guarantees
Sophie Grünbacher, Ramin Hasani, Mathias Lechner, Jacek Cyranka, Scott A. Smolka, and Radu Grosu AAAI Conference on Artificial Intelligence (AAAI) , 2021 |
2020
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Neural
circuit policies enabling auditable
autonomy
Mathias Lechner*, Ramin Hasani*, Alexander Amini, Thomas A. Henzinger, Daniela Rus, and Radu Grosu Nature Machine Intelligence, 2020 |
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The Natural
Lottery
Ticket Winner: Reinforcement Learning with Ordinary Neural
Circuits
Ramin Hasani*, Mathias Lechner*, Alexander Amini, Daniela Rus, and Radu Grosu International Conference on Machine Learning (ICML), 2020 |
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Learning
Representations for binary classification
without backpropagation
Mathias Lechner International Conference on Learning Representations (ICLR), 2020 |
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An SMT Theory of
Fixed-Point Arithmetic
Marek Baranowski, Shaobo He, Mathias Lechner, Thanh Son Nguyen, and Zvonimir Rakamaric International Joint Conference on Automated Reasoning (IJCAR), 2020 |
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Gershgorin Loss Stabilizes the
Recurrent Neural Network Compartment of an End-To-End Robot
Learning
Scheme
Mathias Lechner*, Ramin Hasani*, Daniela Rus, and Radu Grosu IEEE International Conference on Robotics and Automation (ICRA), 2020 |
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How Many Bits Does it Take
to
Quantize Your Neural
Network?
Scheme
Mirco Giacobbe*, Thomas A. Henzinger*, and Mathias Lechner* (alphabetical) International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS), 2020 |
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Lagrangian Reachtubes: The Next
Generation
Sophie Gruenbacher, Jacek Cyranka, Mathias Lechner, Md. Ariful Islam, Scott Smolka, and Radu Grosu TC-DES and TC-HS Outstanding Student Paper Prize IEEE Conference on Decision and Control (CDC), 2020 |
2019
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Response characterization for
auditing cell dynamics in long short-term memory
networks
Ramin Hasani*, Alexander Amini*, Mathias Lechner, Felix Naser, Radu Grosu, and Daniela Rus International Joint Conference on Neural Networks (IJCNN), 2019 |
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Designing
worm-inspired neural networks for
interpretable robotic
control
Mathias Lechner*, Ramin Hasani*, Manuel Zimmer, Thomas A. Henzinger, and Radu Grosu IEEE International Conference on Robotics and Automation (ICRA), 2019 |
Awards
Hyperion Research 2022 HPC Innovation Excellence Award for Liquid Machine Learning
Outstanding Reviewer Award 2021 at the IEEE International Conference on Robotics and Automation (ICRA)
First Place In F1TENTH - Autonomous Racing Grand Prix at IFAC 2020
Distinguished Young Alumnus-Award 2018 Faculty of Informatics at TU Wien