Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing Their Input Gradients
Summary
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing Their Input Gradients is a scholarly article[1].
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Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing Their Input Gradients's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing Their Input Gradients. Retrieved May 24, 2026, from https://4ort.xyz/entity/improving-the-adversarial-robustness-and-interpretability-of-deep-neural-networks-by-regularizing-their-input-gradients
MLA“Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing Their Input Gradients.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/improving-the-adversarial-robustness-and-interpretability-of-deep-neural-networks-by-regularizing-their-input-gradients.
BibTeX@misc{4ortxyz_improving-the-adversarial-robustness-and-interpretability-of-deep-neural-networks-by-regularizing-their-input-gradients_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing Their Input Gradients}}, year = {2026}, url = {https://4ort.xyz/entity/improving-the-adversarial-robustness-and-interpretability-of-deep-neural-networks-by-regularizing-their-input-gradients}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing Their Input Gradients — https://4ort.xyz/entity/improving-the-adversarial-robustness-and-interpretability-of-deep-neural-networks-by-regularizing-their-input-gradients (retrieved 2026-05-24)