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Robustness Certification of Generative Models

, , and . (2020)cite arxiv:2004.14756Comment: Prior version submitted to ICLR 2020.

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Universal Approximation with Certified Networks., , and . CoRR, (2019)Differentiable Abstract Interpretation for Provably Robust Neural Networks., , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 3575-3583. PMLR, (2018)Ten simple rules for using large language models in science, version 1.0., , , , , , , , , and 10 other author(s). PLoS Comput. Biol., (January 2024)Robustness Certification of Generative Models., , and . CoRR, (2020)Online Robustness Training for Deep Reinforcement Learning., , , and . CoRR, (2019)A Provable Defense for Deep Residual Networks., , and . CoRR, (2019)AI2: Safety and Robustness Certification of Neural Networks with Abstract Interpretation., , , , , and . IEEE Symposium on Security and Privacy, page 3-18. IEEE Computer Society, (2018)Robustness certification with generative models., , , , and . PLDI, page 1141-1154. ACM, (2021)Training Neural Machines with Trace-Based Supervision., , , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 3566-3574. PMLR, (2018)LLM Guided Inductive Inference for Solving Compositional Problems., , and . CoRR, (2023)