{"total":20,"rows":[{"id":"2212.05630","title":"DISCO: Adversarial Defense with Local Implicit Functions","created":"2022-12-11","cited_by_count":34,"area":null},{"id":"2304.10550","title":"Deep transfer learning for intrusion detection in industrial control networks: A comprehensive review","created":"2023-04-19","cited_by_count":21,"area":null},{"id":"2307.07187","title":"Erasing, Transforming, and Noising Defense Network for Occluded Person Re-Identification","created":"2023-07-14","cited_by_count":19,"area":null},{"id":"2106.03785","title":"Generative Adversarial Networks: A Survey Towards Private and Secure Applications","created":"2021-06-07","cited_by_count":15,"area":null},{"id":"2306.01485","title":"Robust low-rank training via approximate orthonormal constraints","created":"2023-06-02","cited_by_count":13,"area":null},{"id":"2101.03042","title":"Towards a Robust and Trustworthy Machine Learning System Development: An Engineering Perspective","created":"2021-01-08","cited_by_count":9,"area":null},{"id":"2108.12492","title":"Disrupting Adversarial Transferability in Deep Neural Networks","created":"2021-08-27","cited_by_count":6,"area":null},{"id":"2301.09069","title":"Provable Unrestricted Adversarial Training without Compromise with Generalizability","created":"2023-01-22","cited_by_count":6,"area":null},{"id":"2505.08022","title":"Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks","created":"2025-05-12","cited_by_count":6,"area":null},{"id":"2207.06035","title":"Perturbation Inactivation Based Adversarial Defense for Face Recognition","created":"2022-07-13","cited_by_count":5,"area":null},{"id":"2301.12896","title":"Identifying Adversarially Attackable and Robust Samples","created":"2023-01-30","cited_by_count":5,"area":null},{"id":"2107.05780","title":"Detect and Defense Against Adversarial Examples in Deep Learning using Natural Scene Statistics and Adaptive Denoising","created":"2021-07-12","cited_by_count":3,"area":null},{"id":"2210.14229","title":"Causal Information Bottleneck Boosts Adversarial Robustness of Deep Neural Network","created":"2022-10-25","cited_by_count":3,"area":null},{"id":"2406.18144","title":"Artificial Immune System of Secure Face Recognition Against Adversarial Attacks","created":"2024-06-26","cited_by_count":2,"area":null},{"id":"2103.04513","title":"Improving Global Adversarial Robustness Generalization With Adversarially Trained GAN","created":"2021-03-08","cited_by_count":1,"area":null},{"id":"2108.09713","title":"Robustness-via-Synthesis: Robust Training with Generative Adversarial Perturbations","created":"2021-08-22","cited_by_count":1,"area":null},{"id":"2112.12431","title":"Adaptive Modeling Against Adversarial Attacks","created":"2021-12-23","cited_by_count":0,"area":null},{"id":"2206.10400","title":"Using EBGAN for Anomaly Intrusion Detection","created":"2022-06-21","cited_by_count":0,"area":null},{"id":"2306.04756","title":"A Linearly Convergent GAN Inversion-based Algorithm for Reverse Engineering of Deceptions","created":"2023-06-07","cited_by_count":0,"area":null},{"id":"2307.05095","title":"ATWM: Defense against adversarial malware based on adversarial training","created":"2023-07-11","cited_by_count":0,"area":null}],"next_cursor":null}