Matthew Mirman

15 papers A* 6Journal 8
YearRankTypeTitle / Venue / Authors
2024 J jnl
Ten simple rules for using large language models in science, version 1.0.
PLoS Comput. Biol.
Gabriel Reuben Smith, Carolina Bello, Lalasia Bialic-Murphy, Emily Clark, Camille S. Delavaux, Camille Fournier de Lauriere, Johan van den Hoogen, Thomas Lauber, Haozhi Ma, Daniel S. Maynard, Matthew Mirman, Lidong Mo, Dominic Rebindaine, Josephine Elena Reek, Leland K. Werden, Zhaofei Wu, Gayoung Yang, Qingzhou Zhao, Constantin M. Zohner, Thomas Ward Crowther
2023 J jnl
LLM Guided Inductive Inference for Solving Compositional Problems.
CoRR
Abhigya Sodani, Lauren Moos, Matthew Mirman
2022 — —
Certified Deep Learning: Verification and Training.
Matthew Mirman
2022 J jnl
The Fundamental Limits of Neural Networks for Interval Certified Robustness.
Trans. Mach. Learn. Res.
Matthew Mirman, Maximilian Baader, Martin T. Vechev
2021 A* conf
Robustness certification with generative models.
PLDI
Matthew Mirman, Alexander Hägele, Pavol Bielik, Timon Gehr, Martin T. Vechev
2021 J jnl
The Fundamental Limits of Interval Arithmetic for Neural Networks.
CoRR
Matthew Mirman, Maximilian Baader, Martin T. Vechev
2020 J jnl
Robustness Certification of Generative Models.
CoRR
Matthew Mirman, Timon Gehr, Martin T. Vechev
2020 A* conf
Universal Approximation with Certified Networks.
ICLR
Maximilian Baader, Matthew Mirman, Martin T. Vechev
2019 J jnl
A Provable Defense for Deep Residual Networks.
CoRR
Matthew Mirman, Gagandeep Singh, Martin T. Vechev
2019 J jnl
Online Robustness Training for Deep Reinforcement Learning.
CoRR
Marc Fischer, Matthew Mirman, Steven Stalder, Martin T. Vechev
2019 J jnl
Universal Approximation with Certified Networks.
CoRR
Maximilian Baader, Matthew Mirman, Martin T. Vechev
2018 A* conf
AI2: Safety and Robustness Certification of Neural Networks with Abstract Interpretation.
IEEE Symposium on Security and Privacy
Timon Gehr, Matthew Mirman, Dana Drachsler-Cohen, Petar Tsankov, Swarat Chaudhuri, Martin T. Vechev
2018 A* conf
Differentiable Abstract Interpretation for Provably Robust Neural Networks.
ICML
Matthew Mirman, Timon Gehr, Martin T. Vechev
2018 A* conf
Fast and Effective Robustness Certification.
NeurIPS
Gagandeep Singh, Timon Gehr, Matthew Mirman, Markus Püschel, Martin T. Vechev
2018 A* conf
Training Neural Machines with Trace-Based Supervision.
ICML
Matthew Mirman, Dimitar Dimitrov, Pavle Djordjevic, Timon Gehr, Martin T. Vechev