The author is very grateful to the discussants for sharing their viewpoints on the article. The discussant contributions highlight the gaps in the theoretical understanding and outline many possible directions for future research in this area. The rejoinder is structured according to topics. We refer to [GMMM], [K], [KL], and [S] for the discussant contributions by Ghorbani et al., Kutyniok, Kohler & Langer, and Shamir, respectively.

中文翻译：

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反驳：“使用具有 ReLU 激活函数的深度神经网络的非参数回归”

作者非常感谢讨论者分享他们对文章的观点。讨论者的贡献突出了理论理解上的差距，并概述了该领域未来研究的许多可能方向。反驳是根据主题来组织的。对于 Ghorbani 等人、Kutyniok、Kohler & Langer 和 Shamir 的讨论者贡献，我们分别参考 [GMMM]、[K]、[KL] 和 [S]。