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Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training

, and . (2017)cite arxiv:1705.09199.

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Extending Knowledge Bases Using Images., , and . AKBC@NIPS, OpenReview.net, (2017)The Devil Is in the GAN: Backdoor Attacks and Defenses in Deep Generative Models., , and . ESORICS (3), volume 13556 of Lecture Notes in Computer Science, page 776-783. Springer, (2022)Challenges and Pitfalls of Bayesian Unlearning., , , and . CoRR, (2022)Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training, and . (2017)cite arxiv:1705.09199.Automation of Deep Learning - Theory and Practice., , and . ICMR, page 5-6. ACM, (2020)Towards Consistency of Adversarial Training for Generative Models, and . (2017)cite arxiv:1705.09199.Matching Pairs: Attributing Fine-Tuned Models to their Pre-Trained Large Language Models., , , , , and . ACL (1), page 7423-7442. Association for Computational Linguistics, (2023)Pruning Federated Learning Models for Anomaly Detection in Resource-Constrained Environments., , , , , and . IEEE Big Data, page 3274-3283. IEEE, (2023)Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training., and . AISTATS, volume 84 of Proceedings of Machine Learning Research, page 642-651. PMLR, (2018)A Survey on Neural Architecture Search., , and . CoRR, (2019)