Timon Gehr

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 22

Top Topics

Exact Inference

Abstract Interpretation

Top Venues

Publications

Hristo Venev, Timon Gehr, Dimitar Dimitrov, Martin T. Vechev
Modular Synthesis of Efficient Quantum Uncomputation. CoRR (2024)
Dimitar Iliev Dimitrov, Gagandeep Singh, Timon Gehr, Martin T. Vechev
Provably Robust Adversarial Examples. ICLR (2022)
Matthew Mirman, Alexander Hägele, Pavol Bielik, Timon Gehr, Martin T. Vechev
Robustness certification with generative models. PLDI (2021)
Benjamin Bichsel, Maximilian Baader, Timon Gehr, Martin T. Vechev
Silq: a high-level quantum language with safe uncomputation and intuitive semantics. PLDI (2020)
Dimitar I. Dimitrov, Gagandeep Singh, Timon Gehr, Martin T. Vechev
Scalable Inference of Symbolic Adversarial Examples. CoRR (2020)
Matthew Mirman, Timon Gehr, Martin T. Vechev
Robustness Certification of Generative Models. CoRR (2020)
Timon Gehr, Samuel Steffen, Martin T. Vechev
λPSI: exact inference for higher-order probabilistic programs. PLDI (2020)
Samuel Steffen, Timon Gehr, Petar Tsankov, Laurent Vanbever, Martin T. Vechev
Probabilistic Verification of Network Configurations. SIGCOMM (2020)
Gagandeep Singh, Timon Gehr, Markus Püschel, Martin T. Vechev
An abstract domain for certifying neural networks. Proc. ACM Program. Lang. 3 (POPL) (2019)
Marc Fischer, Mislav Balunovic, Dana Drachsler-Cohen, Timon Gehr, Ce Zhang, Martin T. Vechev
DL2: Training and Querying Neural Networks with Logic. ICML (2019)
Mislav Balunovic, Maximilian Baader, Gagandeep Singh, Timon Gehr, Martin T. Vechev
Certifying Geometric Robustness of Neural Networks. NeurIPS (2019)
Gagandeep Singh, Timon Gehr, Markus Püschel, Martin T. Vechev
Boosting Robustness Certification of Neural Networks. ICLR (Poster) (2019)
Timon Gehr, Sasa Misailovic, Petar Tsankov, Laurent Vanbever, Pascal Wiesmann, Martin T. Vechev
Bayonet: probabilistic inference for networks. PLDI (2018)
Benjamin Bichsel, Timon Gehr, Martin T. Vechev
Fine-Grained Semantics for Probabilistic Programs. ESOP (2018)
Benjamin Bichsel, Timon Gehr, Dana Drachsler-Cohen, Petar Tsankov, Martin T. Vechev
DP-Finder: Finding Differential Privacy Violations by Sampling and Optimization. CCS (2018)
Gagandeep Singh, Timon Gehr, Matthew Mirman, Markus Püschel, Martin T. Vechev
Fast and Effective Robustness Certification. NeurIPS (2018)
Timon Gehr, Matthew Mirman, Dana Drachsler-Cohen, Petar Tsankov, Swarat Chaudhuri, Martin T. Vechev
AI2: Safety and Robustness Certification of Neural Networks with Abstract Interpretation. IEEE Symposium on Security and Privacy (2018)
Matthew Mirman, Timon Gehr, Martin T. Vechev
Differentiable Abstract Interpretation for Provably Robust Neural Networks. ICML (2018)
Marco Cusumano-Towner, Benjamin Bichsel, Timon Gehr, Martin T. Vechev, Vikash K. Mansinghka
Incremental inference for probabilistic programs. PLDI (2018)
Matthew Mirman, Dimitar K. Dimitrov, Pavle Djordjevic, Timon Gehr, Martin T. Vechev
Training Neural Machines with Trace-Based Supervision. ICML (2018)
Martin Kucera, Petar Tsankov, Timon Gehr, Marco Guarnieri, Martin T. Vechev
Synthesis of Probabilistic Privacy Enforcement. CCS (2017)
Timon Gehr, Sasa Misailovic, Martin T. Vechev
PSI: Exact Symbolic Inference for Probabilistic Programs. CAV (1) (2016)
Timon Gehr, Dimitar K. Dimitrov, Martin T. Vechev
Learning Commutativity Specifications. CAV (1) (2015)