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Mathias Lechner
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2020 – today
- 2024
- [c36]Noel Loo, Ramin M. Hasani, Mathias Lechner, Alexander Amini, Daniela Rus:
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation. ICLR 2024 - [c35]Neehal Tumma, Mathias Lechner, Noel Loo, Ramin M. Hasani, Daniela Rus:
Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control. ICLR 2024 - [c34]Noel Loo, Alaa Maalouf, Ramin M. Hasani, Mathias Lechner, Alexander Amini, Daniela Rus:
Large Scale Dataset Distillation with Domain Shift. ICML 2024 - [c33]Rom N. Parnichkun, Stefano Massaroli, Alessandro Moro, Jimmy T. H. Smith, Ramin M. Hasani, Mathias Lechner, Qi An, Christopher Ré, Hajime Asama, Stefano Ermon, Taiji Suzuki, Michael Poli, Atsushi Yamashita:
State-Free Inference of State-Space Models: The *Transfer Function* Approach. ICML 2024 - [c32]Mathias Lechner, Ramin M. Hasani, Alexander Amini, Tsun-Hsuan Wang, Thomas A. Henzinger, Daniela Rus:
Overparametrization helps offline-to-online generalization of closed-loop control from pixels. ICRA 2024: 2774-2782 - [c31]Mónika Farsang, Mathias Lechner, David Lung, Ramin M. Hasani, Daniela Rus, Radu Grosu:
Learning with Chemical versus Electrical Synapses Does it Make a Difference? ICRA 2024: 15106-15112 - [i38]Mónika Farsang, Mathias Lechner, David Lung, Ramin M. Hasani, Daniela Rus, Radu Grosu:
Learning with Chemical versus Electrical Synapses - Does it Make a Difference? CoRR abs/2401.08602 (2024) - [i37]Rom N. Parnichkun, Stefano Massaroli, Alessandro Moro, Jimmy T. H. Smith, Ramin M. Hasani, Mathias Lechner, Qi An, Christopher Ré, Hajime Asama, Stefano Ermon, Taiji Suzuki, Atsushi Yamashita, Michael Poli:
State-Free Inference of State-Space Models: The Transfer Function Approach. CoRR abs/2405.06147 (2024) - 2023
- [j6]Mathias Lechner
, Alexander Amini
Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning. IEEE Robotics Autom. Lett. 8(3): 1595-1602 (2023) - [j5]Makram Chahine
Robust flight navigation out of distribution with liquid neural networks. Sci. Robotics 8(77) (2023) - [c30]Dorde Zikelic, Mathias Lechner, Thomas A. Henzinger, Krishnendu Chatterjee:
Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees. AAAI 2023: 11926-11935 - [c29]Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, Thomas A. Henzinger, Daniela Rus:
Quantization-Aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks. AAAI 2023: 14964-14973 - [c28]Matin Ansaripour, Krishnendu Chatterjee
Learning Provably Stabilizing Neural Controllers for Discrete-Time Stochastic Systems. ATVA (1) 2023: 357-379 - [c27]Ramin M. Hasani, Mathias Lechner, Tsun-Hsuan Wang, Makram Chahine, Alexander Amini, Daniela Rus:
Liquid Structural State-Space Models. ICLR 2023 - [c26]Noel Loo, Ramin M. Hasani, Mathias Lechner, Daniela Rus:
Dataset Distillation with Convexified Implicit Gradients. ICML 2023: 22649-22674 - [c25]Wei Xiao, Tsun-Hsuan Wang, Ramin M. Hasani, Mathias Lechner, Yutong Ban, Chuang Gan, Daniela Rus:
On the Forward Invariance of Neural ODEs. ICML 2023: 38100-38124 - [c24]Noam Buckman, Shiva Sreeram, Mathias Lechner, Yutong Ban, Ramin M. Hasani, Sertac Karaman, Daniela Rus:
Infrastructure-based End-to-End Learning and Prevention of Driver Failure. ICRA 2023: 3576-3583 - [c23]Lianhao Yin, Makram Chahine, Tsun-Hsuan Wang, Tim Seyde, Chao Liu, Mathias Lechner, Ramin M. Hasani, Daniela Rus:
Towards Cooperative Flight Control Using Visual-Attention. IROS 2023: 6334-6341 - [c22]Mathias Lechner, Lianhao Yin, Tim Seyde, Tsun-Hsuan Johnson Wang, Wei Xiao, Ramin M. Hasani, Joshua Rountree, Daniela Rus:
Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning. NeurIPS 2023 - [c21]Alaa Maalouf, Murad Tukan, Noel Loo, Ramin M. Hasani, Mathias Lechner, Daniela Rus:
On the Size and Approximation Error of Distilled Datasets. NeurIPS 2023 - [c20]Dorde Zikelic, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee, Thomas A. Henzinger:
Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees. NeurIPS 2023 - [c19]Krishnendu Chatterjee, Thomas A. Henzinger, Mathias Lechner, Dorde Zikelic:
A Learner-Verifier Framework for Neural Network Controllers and Certificates of Stochastic Systems. TACAS (1) 2023: 3-25 - [i36]Noel Loo, Ramin M. Hasani, Mathias Lechner, Daniela Rus:
Dataset Distillation Fixes Dataset Reconstruction Attacks. CoRR abs/2302.01428 (2023) - [i35]Noel Loo, Ramin M. Hasani, Mathias Lechner, Daniela Rus:
Dataset Distillation with Convexified Implicit Gradients. CoRR abs/2302.06755 (2023) - [i34]Noam Buckman, Shiva Sreeram, Mathias Lechner, Yutong Ban, Ramin M. Hasani, Sertac Karaman, Daniela Rus:
Infrastructure-based End-to-End Learning and Prevention of Driver Failure. CoRR abs/2303.12224 (2023) - [i33]Alaa Maalouf, Murad Tukan, Noel Loo, Ramin M. Hasani, Mathias Lechner, Daniela Rus:
On the Size and Approximation Error of Distilled Sets. CoRR abs/2305.14113 (2023) - [i32]Neehal Tumma, Mathias Lechner, Noel Loo, Ramin M. Hasani, Daniela Rus:
Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control. CoRR abs/2310.03915 (2023) - [i31]Dorde Zikelic, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee, Thomas A. Henzinger:
Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees. CoRR abs/2312.01456 (2023) - 2022
- [j4]Ramin M. Hasani
Closed-form continuous-time neural networks. Nat. Mac. Intell. 4(11): 992-1003 (2022) - [j3]Ramin M. Hasani
Publisher Correction: Closed-form continuous-time neural networks. Nat. Mac. Intell. 4(12): 1267 (2022) - [c18]Sophie A. Gruenbacher, Mathias Lechner, Ramin M. Hasani, Daniela Rus, Thomas A. Henzinger, Scott A. Smolka, Radu Grosu:
GoTube: Scalable Statistical Verification of Continuous-Depth Models. AAAI 2022: 6755-6764 - [c17]Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, Thomas A. Henzinger:
Stability Verification in Stochastic Control Systems via Neural Network Supermartingales. AAAI 2022: 7326-7336 - [c16]Axel Brunnbauer, Luigi Berducci, Andreas Brandstätter
Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing. ICRA 2022: 7513-7520 - [i30]Mathias Lechner, Alexander Amini, Daniela Rus, Thomas A. Henzinger:
Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning. CoRR abs/2204.07373 (2022) - [i29]Dorde Zikelic, Mathias Lechner, Krishnendu Chatterjee, Thomas A. Henzinger:
Learning Stabilizing Policies in Stochastic Control Systems. CoRR abs/2205.11991 (2022) - [i28]Mathias Lechner, Ramin M. Hasani, Zahra Babaiee, Radu Grosu, Daniela Rus, Thomas A. Henzinger, Sepp Hochreiter:
Entangled Residual Mappings. CoRR abs/2206.01261 (2022) - [i27]Ramin M. Hasani, Mathias Lechner, Tsun-Hsuan Wang, Makram Chahine, Alexander Amini, Daniela Rus:
Liquid Structural State-Space Models. CoRR abs/2209.12951 (2022) - [i26]Mathias Lechner, Ramin M. Hasani, Alexander Amini, Tsun-Hsuan Wang, Thomas A. Henzinger, Daniela Rus:
Are All Vision Models Created Equal? A Study of the Open-Loop to Closed-Loop Causality Gap. CoRR abs/2210.04303 (2022) - [i25]Mathias Lechner, Ramin M. Hasani, Philipp Neubauer, Sophie A. Neubauer, Daniela Rus:
PyHopper - Hyperparameter optimization. CoRR abs/2210.04728 (2022) - [i24]Wei Xiao, Tsun-Hsuan Wang, Ramin M. Hasani, Mathias Lechner, Daniela Rus:
On the Forward Invariance of Neural ODEs. CoRR abs/2210.04763 (2022) - [i23]Matin Ansaripour, Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, Thomas A. Henzinger:
Learning Control Policies for Region Stabilization in Stochastic Systems. CoRR abs/2210.05304 (2022) - [i22]Dorde Zikelic, Mathias Lechner, Thomas A. Henzinger, Krishnendu Chatterjee:
Learning Control Policies for Stochastic Systems with Reach-avoid Guarantees. CoRR abs/2210.05308 (2022) - [i21]Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, Thomas A. Henzinger, Daniela Rus:
Quantization-aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks. CoRR abs/2211.16187 (2022) - [i20]Lianhao Yin, Tsun-Hsuan Wang, Makram Chahine, Tim Seyde, Mathias Lechner, Ramin M. Hasani, Daniela Rus:
Cooperative Flight Control Using Visual-Attention - Air-Guardian. CoRR abs/2212.11084 (2022) - 2021
- [j2]Stefan Sietzen, Mathias Lechner
Interactive Analysis of CNN Robustness. Comput. Graph. Forum 40(7): 253-264 (2021) - [c15]Thomas A. Henzinger, Mathias Lechner, Dorde Zikelic:
Scalable Verification of Quantized Neural Networks. AAAI 2021: 3787-3795 - [c14]Ramin M. Hasani, Mathias Lechner, Alexander Amini, Daniela Rus, Radu Grosu:
Liquid Time-constant Networks. AAAI 2021: 7657-7666 - [c13]Sophie Gruenbacher, Ramin M. Hasani, Mathias Lechner, Jacek Cyranka, Scott A. Smolka, Radu Grosu:
On the Verification of Neural ODEs with Stochastic Guarantees. AAAI 2021: 11525-11535 - [c12]Zahra Babaiee, Ramin M. Hasani, Mathias Lechner, Daniela Rus, Radu Grosu:
On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification. ICML 2021: 478-489 - [c11]Mathias Lechner, Ramin M. Hasani, Radu Grosu, Daniela Rus, Thomas A. Henzinger:
Adversarial Training is Not Ready for Robot Learning. ICRA 2021: 4140-4147 - [c10]Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, Thomas A. Henzinger:
Infinite Time Horizon Safety of Bayesian Neural Networks. NeurIPS 2021: 10171-10185 - [c9]Charles Vorbach, Ramin M. Hasani, Alexander Amini, Mathias Lechner, Daniela Rus:
Causal Navigation by Continuous-time Neural Networks. NeurIPS 2021: 12425-12440 - [i19]Axel Brunnbauer, Luigi Berducci, Andreas Brandstätter
Model-based versus Model-free Deep Reinforcement Learning for Autonomous Racing Cars. CoRR abs/2103.04909 (2021) - [i18]Mathias Lechner, Ramin M. Hasani, Radu Grosu, Daniela Rus, Thomas A. Henzinger:
Adversarial Training is Not Ready for Robot Learning. CoRR abs/2103.08187 (2021) - [i17]Zahra Babaiee, Ramin M. Hasani, Mathias Lechner, Daniela Rus, Radu Grosu:
On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification. CoRR abs/2106.07091 (2021) - [i16]Charles Vorbach, Ramin M. Hasani, Alexander Amini, Mathias Lechner, Daniela Rus:
Causal Navigation by Continuous-time Neural Networks. CoRR abs/2106.08314 (2021) - [i15]Ramin M. Hasani, Mathias Lechner, Alexander Amini, Lucas Liebenwein, Max Tschaikowski, Gerald Teschl, Daniela Rus:
Closed-form Continuous-Depth Models. CoRR abs/2106.13898 (2021) - [i14]Sophie Gruenbacher, Mathias Lechner, Ramin M. Hasani, Daniela Rus, Thomas A. Henzinger, Scott A. Smolka, Radu Grosu:
GoTube: Scalable Stochastic Verification of Continuous-Depth Models. CoRR abs/2107.08467 (2021) - [i13]Stefan Sietzen, Mathias Lechner, Judy Borowski, Ramin M. Hasani, Manuela Waldner:
Interactive Analysis of CNN Robustness. CoRR abs/2110.07667 (2021) - [i12]Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, Thomas A. Henzinger:
Infinite Time Horizon Safety of Bayesian Neural Networks. CoRR abs/2111.03165 (2021) - [i11]Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, Thomas A. Henzinger:
Stability Verification in Stochastic Control Systems via Neural Network Supermartingales. CoRR abs/2112.09495 (2021) - 2020
- [j1]Mathias Lechner
Neural circuit policies enabling auditable autonomy. Nat. Mach. Intell. 2(10): 642-652 (2020) - [c8]Marek S. Baranowski, Shaobo He, Mathias Lechner, Thanh Son Nguyen, Zvonimir Rakamaric:
An SMT Theory of Fixed-Point Arithmetic. IJCAR (1) 2020: 13-31 - [c7]Sophie Gruenbacher, Jacek Cyranka, Mathias Lechner, Md. Ariful Islam, Scott A. Smolka, Radu Grosu:
Lagrangian Reachtubes: The Next Generation. CDC 2020: 1556-1563 - [c6]Mathias Lechner:
Learning representations for binary-classification without backpropagation. ICLR 2020 - [c5]Ramin M. Hasani, Mathias Lechner, Alexander Amini, Daniela Rus, Radu Grosu:
A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits. ICML 2020: 4082-4093 - [c4]Mathias Lechner, Ramin M. Hasani, Daniela Rus, Radu Grosu:
Gershgorin Loss Stabilizes the Recurrent Neural Network Compartment of an End-to-end Robot Learning Scheme. ICRA 2020: 5446-5452 - [c3]Mirco Giacobbe
How Many Bits Does it Take to Quantize Your Neural Network? TACAS (2) 2020: 79-97 - [i10]Mathias Lechner, Ramin M. Hasani:
Learning Long-Term Dependencies in Irregularly-Sampled Time Series. CoRR abs/2006.04418 (2020) - [i9]Ramin M. Hasani, Mathias Lechner, Alexander Amini, Daniela Rus, Radu Grosu:
Liquid Time-constant Networks. CoRR abs/2006.04439 (2020) - [i8]Sophie Gruenbacher, Jacek Cyranka, Mathias Lechner, Md. Ariful Islam, Scott A. Smolka, Radu Grosu:
Lagrangian Reachtubes: The Next Generation. CoRR abs/2012.07458 (2020) - [i7]Thomas A. Henzinger, Mathias Lechner, Dorde Zikelic:
Scalable Verification of Quantized Neural Networks (Technical Report). CoRR abs/2012.08185 (2020) - [i6]Sophie Gruenbacher, Ramin M. Hasani, Mathias Lechner, Jacek Cyranka, Scott A. Smolka, Radu Grosu:
On The Verification of Neural ODEs with Stochastic Guarantees. CoRR abs/2012.08863 (2020)
2010 – 2019
- 2019
- [c2]Mathias Lechner, Ramin M. Hasani
Designing Worm-inspired Neural Networks for Interpretable Robotic Control. ICRA 2019: 87-94 - [c1]Ramin M. Hasani
Response Characterization for Auditing Cell Dynamics in Long Short-term Memory Networks. IJCNN 2019: 1-8 - 2018
- [i5]Mathias Lechner, Ramin M. Hasani, Radu Grosu:
Neuronal Circuit Policies. CoRR abs/1803.08554 (2018) - [i4]Ramin M. Hasani, Alexander Amini, Mathias Lechner, Felix Naser, Radu Grosu, Daniela Rus:
Response Characterization for Auditing Cell Dynamics in Long Short-term Memory Networks. CoRR abs/1809.03864 (2018) - [i3]Ramin M. Hasani, Mathias Lechner, Alexander Amini, Daniela Rus, Radu Grosu:
Re-purposing Compact Neuronal Circuit Policies to Govern Reinforcement Learning Tasks. CoRR abs/1809.04423 (2018) - [i2]Ramin M. Hasani, Mathias Lechner, Alexander Amini, Daniela Rus, Radu Grosu:
Liquid Time-constant Recurrent Neural Networks as Universal Approximators. CoRR abs/1811.00321 (2018) - 2017
- [i1]Mathias Lechner, Radu Grosu, Ramin M. Hasani:
Worm-level Control through Search-based Reinforcement Learning. CoRR abs/1711.03467 (2017)
Coauthor Index
[c36] [c35] [c34] [c33] [c32] [c31] [i38] [i37] [j5] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [i36] [i35] [i34] [i33] [i32] [j4] [j3] [c18] [c16] [i28] [i27] [i26] [i25] [i24] [i20] [j2] [c14] [c13] [c12] [c11] [c9] [i19] [i18] [i17] [i16] [i15] [i14] [i13] [j1] [c5] [c4] [i10] [i9] [i6] [c2] [c1] [i5] [i4] [i3] [i2] [i1]
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