| ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models PY Chen*, H Zhang*, Y Sharma, J Yi, CJ Hsieh ACM Workshop on AI and Security (*equal contribution, best paper award finalist), 2017 | 1980 | 2017 |
| Efficient Neural Network Robustness Certification with General Activation Functions H Zhang, TW Weng, PY Chen, CJ Hsieh, L Daniel NeurIPS 2018, 2018 | 804 | 2018 |
| Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives A Dhurandhar*, PY Chen*, R Luss, CC Tu, P Ting, K Shanmugam, P Das NeurIPS 2018 (*equal contribution), 2018 | 675 | 2018 |
| EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples PY Chen*, Y Sharma*, H Zhang, J Yi, CJ Hsieh AAAI 2018 (*equal contribution), 2017 | 658 | 2017 |
| DBA: Distributed Backdoor Attacks against Federated Learning C Xie, K Huang, PY Chen, B Li ICLR 2020, 2019 | 635 | 2019 |
| Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach TW Weng, H Zhang, PY Chen, J Yi, D Su, Y Gao, CJ Hsieh, L Daniel ICLR 2018, 2018 | 526 | 2018 |
| One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques V Arya, RKE Bellamy, PY Chen, A Dhurandhar, M Hind, SC Hoffman, ... arXiv preprint arXiv:1909.03012, 2019 | 498* | 2019 |
| Query-efficient hard-label black-box attack: An optimization-based approach M Cheng, T Le, PY Chen, J Yi, H Zhang, CJ Hsieh ICLR 2019, 2018 | 454 | 2018 |
| Is Robustness the Cost of Accuracy?--A Comprehensive Study on the Robustness of 18 Deep Image Classification Models D Su, H Zhang, H Chen, J Yi, PY Chen, Y Gao ECCV 2018, 2018 | 440 | 2018 |
| AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks CC Tu*, P Ting*, PY Chen*, S Liu, H Zhang, J Yi, CJ Hsieh, SM Cheng AAAI 2019 (oral presentation, *equal contribution), 2018 | 424 | 2018 |
| Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective K Xu, H Chen, S Liu, PY Chen, TW Weng, M Hong, X Lin IJCAI 2019, 2019 | 398 | 2019 |
| Adversarial t-shirt! evading person detectors in a physical world K Xu, G Zhang, S Liu, Q Fan, M Sun, H Chen, PY Chen, Y Wang, X Lin ECCV 2020 (spotlight), 2019 | 358 | 2019 |
| Variational Quantum Circuits for Deep Reinforcement Learning S Yen-Chi Chen, CH Huck Yang, J Qi, PY Chen, X Ma, HS Goan IEEE ACCESS, 2020 | 285 | 2020 |
| Vision transformers are robust learners S Paul*, PY Chen* AAAI 2022 (*equal contribution), 2021 | 284 | 2021 |
| Seq2sick: Evaluating the robustness of sequence-to-sequence models with adversarial examples M Cheng, J Yi, PY Chen, H Zhang, CJ Hsieh AAAI 2020, 2018 | 258 | 2018 |
| Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations P Das, T Sercu, K Wadhawan, I Padhi, S Gehrmann, F Cipcigan, ... Nature Biomedical Engineering 5 (6), 613-623, 2021 | 254 | 2021 |
| Smart attacks in smart grid communication networks PY Chen, SM Cheng, KC Chen IEEE Communications Magazine 50 (8), 24-29, 2012 | 237 | 2012 |
| Sign-OPT: A Query-Efficient Hard-label Adversarial Attack M Cheng, S Singh, P Chen, PY Chen, S Liu, CJ Hsieh ICLR 2020, 2019 | 228 | 2019 |
| System and methods for automated detection, reasoning and recommendations for resilient cyber systems S Choudhury, K Agarwal, PY Chen, I Ray US Patent 10,855,706, 2020 | 218 | 2020 |
| Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness P Zhao, PY Chen, P Das, KN Ramamurthy, X Lin ICLR 2020, 2020 | 196 | 2020 |
Sijia LiuMichigan State University & MIT-IBM Watson AI Lab在 msu.edu 的电子邮件经过验证
