Timon Gehr

According to our database, Timon Gehr authored at least 25 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Modular Synthesis of Efficient Quantum Uncomputation.

Hristo Venev, Timon Gehr, Dimitar I. Dimitrov, Martin T. Vechev

Proc. ACM Program. Lang., 2024

AlphaIntegrator: Transformer Action Search for Symbolic Integration Proofs.

Mert Ünsal, Timon Gehr, Martin T. Vechev

CoRR, 2024

2022

Symbolic Methods for Machine Intelligence.

Timon Gehr

PhD thesis, 2022

Provably Robust Adversarial Examples.

Dimitar Iliev Dimitrov, Gagandeep Singh, Timon Gehr, Martin T. Vechev

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Robustness certification with generative models.

Matthew Mirman, Alexander Hägele, Pavol Bielik, Timon Gehr, Martin T. Vechev

Proceedings of the PLDI '21: 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation, 2021

2020

Scalable Inference of Symbolic Adversarial Examples.

Dimitar I. Dimitrov, Gagandeep Singh, Timon Gehr, Martin T. Vechev

CoRR, 2020

Robustness Certification of Generative Models.

Matthew Mirman, Timon Gehr, Martin T. Vechev

CoRR, 2020

Probabilistic Verification of Network Configurations.

Samuel Steffen, Timon Gehr, Petar Tsankov, Laurent Vanbever, Martin T. Vechev

Proceedings of the SIGCOMM '20: Proceedings of the 2020 Annual conference of the ACM Special Interest Group on Data Communication on the applications, 2020

λPSI: exact inference for higher-order probabilistic programs.

Timon Gehr, Samuel Steffen, Martin T. Vechev

Proceedings of the 41st ACM SIGPLAN International Conference on Programming Language Design and Implementation, 2020

Silq: a high-level quantum language with safe uncomputation and intuitive semantics.

Benjamin Bichsel, Maximilian Baader, Timon Gehr, Martin T. Vechev

Proceedings of the 41st ACM SIGPLAN International Conference on Programming Language Design and Implementation, 2020

2019

An abstract domain for certifying neural networks.

Gagandeep Singh, Timon Gehr, Markus Püschel, Martin T. Vechev

Proc. ACM Program. Lang., 2019

Certifying Geometric Robustness of Neural Networks.

Mislav Balunovic, Maximilian Baader, Gagandeep Singh, Timon Gehr, Martin T. Vechev

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

DL2: Training and Querying Neural Networks with Logic.

Marc Fischer, Mislav Balunovic, Dana Drachsler-Cohen, Timon Gehr, Ce Zhang, Martin T. Vechev

Proceedings of the 36th International Conference on Machine Learning, 2019

Boosting Robustness Certification of Neural Networks.

Gagandeep Singh, Timon Gehr, Markus Püschel, Martin T. Vechev

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

AI2: Safety and Robustness Certification of Neural Networks with Abstract Interpretation.

Timon Gehr, Matthew Mirman, Dana Drachsler-Cohen, Petar Tsankov, Swarat Chaudhuri, Martin T. Vechev

Proceedings of the 2018 IEEE Symposium on Security and Privacy, 2018

Bayonet: probabilistic inference for networks.

Timon Gehr, Sasa Misailovic, Petar Tsankov, Laurent Vanbever, Pascal Wiesmann, Martin T. Vechev

Proceedings of the 39th ACM SIGPLAN Conference on Programming Language Design and Implementation, 2018

Incremental inference for probabilistic programs.

Marco F. Cusumano-Towner, Benjamin Bichsel, Timon Gehr, Martin T. Vechev, Vikash K. Mansinghka

Proceedings of the 39th ACM SIGPLAN Conference on Programming Language Design and Implementation, 2018

Fast and Effective Robustness Certification.

Gagandeep Singh, Timon Gehr, Matthew Mirman, Markus Püschel, Martin T. Vechev

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Differentiable Abstract Interpretation for Provably Robust Neural Networks.

Matthew Mirman, Timon Gehr, Martin T. Vechev

Proceedings of the 35th International Conference on Machine Learning, 2018

Training Neural Machines with Trace-Based Supervision.

Matthew Mirman, Dimitar K. Dimitrov, Pavle Djordjevic, Timon Gehr, Martin T. Vechev

Proceedings of the 35th International Conference on Machine Learning, 2018

Fine-Grained Semantics for Probabilistic Programs.

Benjamin Bichsel, Timon Gehr, Martin T. Vechev

Proceedings of the Programming Languages and Systems, 2018

DP-Finder: Finding Differential Privacy Violations by Sampling and Optimization.

Benjamin Bichsel, Timon Gehr, Dana Drachsler-Cohen, Petar Tsankov, Martin T. Vechev

Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, 2018

2017

Synthesis of Probabilistic Privacy Enforcement.

Martin Kucera, Petar Tsankov, Timon Gehr, Marco Guarnieri, Martin T. Vechev

Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, 2017

2016

PSI: Exact Symbolic Inference for Probabilistic Programs.

Timon Gehr, Sasa Misailovic, Martin T. Vechev

Proceedings of the Computer Aided Verification - 28th International Conference, 2016

2015

Learning Commutativity Specifications.

Timon Gehr, Dimitar K. Dimitrov, Martin T. Vechev

Proceedings of the Computer Aided Verification - 27th International Conference, 2015