# Is AmI (Attacks Meet Interpretability) Robust to Adversarial Examples?

arXiv: https://arxiv.org/abs/1902.02322 · HTML: https://mlsanity.com/paper/1902.02322/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Feb 2019.

## Built on by (most cited first, 7 of 7)

- [A Comprehensive Evaluation Framework for Deep Model Robustness](https://mlsanity.com/paper/2101.09617/) (2021)
- [Improving Robustness by Enhancing Weak Subnets](https://mlsanity.com/paper/2201.12765/) (2022)
- [Efficient Adversarial Training With Data Pruning](https://mlsanity.com/paper/2207.00694/) (2022)
- [Revisiting adversarial training for the worst-performing class](https://mlsanity.com/paper/2302.08872/) (2023)
- [Downlink Power Allocation in Massive MIMO via Deep Learning: Adversarial Attacks and Training](https://mlsanity.com/paper/2206.06592/) (2022)
- [Enhancing Adversarial Example Detection Through Model Explanation](https://mlsanity.com/paper/2503.09735/) (2025)
- [Adversarially Robust PAC Learning with Optimal VC Rates](https://mlsanity.com/paper/2609.24260/) (2026)

## Abstract (arXiv)

No.