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391 Publications
2020 |Published| Conference Paper | IST-REx-ID: 9632 |
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Singh, S. P., & Alistarh, D.-A. (2020). WoodFisher: Efficient second-order approximation for neural network compression. In Advances in Neural Information Processing Systems (Vol. 33, pp. 18098–18109). Vancouver, Canada: Curran Associates.
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2020 |Published| Conference Paper | IST-REx-ID: 9103 |
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Gruenbacher, S., Cyranka, J., Lechner, M., Islam, M. A., Smolka, S. A., & Grosu, R. (2020). Lagrangian reachtubes: The next generation. In Proceedings of the 59th IEEE Conference on Decision and Control (Vol. 2020, pp. 1556–1563). Jeju Islang, Korea (South): IEEE. https://doi.org/10.1109/CDC42340.2020.9304042
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2020 |Published| Conference Paper | IST-REx-ID: 10672 |
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Lechner, M. (2020). Learning representations for binary-classification without backpropagation. In 8th International Conference on Learning Representations. Virtual ; Addis Ababa, Ethiopia: ICLR.
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2020 |Published| Conference Paper | IST-REx-ID: 7808 |
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Giacobbe, M., Henzinger, T. A., & Lechner, M. (2020). 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 (Vol. 12079, pp. 79–97). Dublin, Ireland: Springer Nature. https://doi.org/10.1007/978-3-030-45237-7_5
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2020 |Published| Journal Article | IST-REx-ID: 6761 |
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Avni, G., Henzinger, T. A., & Kupferman, O. (2020). Dynamic resource allocation games. Theoretical Computer Science. Elsevier. https://doi.org/10.1016/j.tcs.2019.06.031
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2020 |Published| Conference Paper | IST-REx-ID: 7505 |
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Henzinger, T. A., Lukina, A., & Schilling, C. (2020). Outside the box: Abstraction-based monitoring of neural networks. In 24th European Conference on Artificial Intelligence (Vol. 325, pp. 2433–2440). Santiago de Compostela, Spain: IOS Press. https://doi.org/10.3233/FAIA200375
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| arXiv
2020 |Published| Conference Paper | IST-REx-ID: 8194 |
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Baranowski, M., He, S., Lechner, M., Nguyen, T. S., & Rakamarić, Z. (2020). An SMT theory of fixed-point arithmetic. In Automated Reasoning (Vol. 12166, pp. 13–31). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-030-51074-9_2
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2020 |Published| Journal Article | IST-REx-ID: 8679
Lechner, M., Hasani, R., Amini, A., Henzinger, T. A., Rus, D., & Grosu, R. (2020). Neural circuit policies enabling auditable autonomy. Nature Machine Intelligence. Springer Nature. https://doi.org/10.1038/s42256-020-00237-3
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2020 |Published| Conference Paper | IST-REx-ID: 8704 |
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Lechner, M., Hasani, R., Rus, D., & Grosu, R. (2020). 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 (pp. 5446–5452). Paris, France: IEEE. https://doi.org/10.1109/ICRA40945.2020.9196608
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2020 |Published| Conference Paper | IST-REx-ID: 8750 |
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Forets, M., Freire, D., & Schilling, C. (2020). Efficient reachability analysis of parametric linear hybrid systems with time-triggered transitions. In 18th ACM-IEEE International Conference on Formal Methods and Models for System Design. Virtual Conference: IEEE. https://doi.org/10.1109/MEMOCODE51338.2020.9314994
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2020 |Published| Conference Paper | IST-REx-ID: 8287 |
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Bogomolov, S., Forets, M., Frehse, G., Potomkin, K., & Schilling, C. (2020). Reachability analysis of linear hybrid systems via block decomposition. In Proceedings of the International Conference on Embedded Software. Virtual .
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2020 |Published| Journal Article | IST-REx-ID: 8790 |
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Bogomolov, S., Forets, M., Frehse, G., Potomkin, K., & Schilling, C. (2020). Reachability analysis of linear hybrid systems via block decomposition. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. IEEE. https://doi.org/10.1109/TCAD.2020.3012859
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| arXiv
2020 |Published| Journal Article | IST-REx-ID: 9197
Avni, G., Ibsen-Jensen, R., & Tkadlec, J. (2020). All-pay bidding games on graphs. Proceedings of the AAAI Conference on Artificial Intelligence. New York, NY, United States: Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v34i02.5546
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| arXiv
2020 |Published| Conference Paper | IST-REx-ID: 8623 |
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Henzinger, T. A., & Sarac, N. E. (2020). Monitorability under assumptions. In Runtime Verification (Vol. 12399, pp. 3–18). Los Angeles, CA, United States: Springer Nature. https://doi.org/10.1007/978-3-030-60508-7_1
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2020 |Published| Conference Paper | IST-REx-ID: 8195 |
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Kragl, B., Qadeer, S., & Henzinger, T. A. (2020). Refinement for structured concurrent programs. In Computer Aided Verification (Vol. 12224, pp. 275–298). Springer Nature. https://doi.org/10.1007/978-3-030-53288-8_14
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2020 |Published| Conference Paper | IST-REx-ID: 8012 |
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Kragl, B., Enea, C., Henzinger, T. A., Mutluergil, S. O., & Qadeer, S. (2020). Inductive sequentialization of asynchronous programs. In Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation (pp. 227–242). London, United Kingdom: Association for Computing Machinery. https://doi.org/10.1145/3385412.3385980
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2020 |Published| Journal Article | IST-REx-ID: 10861
Nickovic, D., Lebeltel, O., Maler, O., Ferrere, T., & Ulus, D. (2020). AMT 2.0: Qualitative and quantitative trace analysis with extended signal temporal logic. International Journal on Software Tools for Technology Transfer. Springer Nature. https://doi.org/10.1007/s10009-020-00582-z
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2020 |Published| Thesis | IST-REx-ID: 8332 |
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Kragl, B. (2020). Verifying concurrent programs: Refinement, synchronization, sequentialization. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:8332
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2020 |Published| Conference Paper | IST-REx-ID: 9202 |
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Garcia Soto, M., & Prabhakar, P. (2020). Hybridization for stability verification of nonlinear switched systems. In 2020 IEEE Real-Time Systems Symposium (pp. 244–256). Houston, TX, USA : IEEE. https://doi.org/10.1109/RTSS49844.2020.00031
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2020 |Published| Journal Article | IST-REx-ID: 7426 |
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Garcia Soto, M., & Prabhakar, P. (2020). Abstraction based verification of stability of polyhedral switched systems. Nonlinear Analysis: Hybrid Systems. Elsevier. https://doi.org/10.1016/j.nahs.2020.100856
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