Follow
Jiefeng Chen
Jiefeng Chen
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining
J Chen, Y Li, X Wu, Y Liang, S Jha
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021
1232021
Robust Out-of-distribution Detection for Neural Networks
J Chen, Y Li, X Wu, Y Liang, S Jha
arXiv preprint arXiv:2003.09711, 2020
832020
Robust Attribution Regularization
J Chen, X Wu, V Rastogi, Y Liang, S Jha
arXiv preprint arXiv:1905.09957, 2019
802019
Concise Explanations of Neural Networks using Adversarial Training
P Chalasani, J Chen, AR Chowdhury, S Jha, X Wu
International Conference on Machine Learning, 2020
682020
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles
J Chen, F Liu, B Avci, X Wu, Y Liang, S Jha
Advances in Neural Information Processing Systems 34, 2021
572021
AI-GAN: Attack-inspired generation of adversarial examples
T Bai, J Zhao, J Zhu, S Han, J Chen, B Li, A Kot
2021 IEEE International Conference on Image Processing (ICIP), 2543-2547, 2021
542021
Towards Understanding Limitations of Pixel Discretization Against Adversarial Attacks
J Chen, X Wu, V Rastogi, Y Liang, S Jha
arXiv preprint arXiv:1805.07816, 2018
40*2018
Reinforcing adversarial robustness using model confidence induced by adversarial training
X Wu, U Jang, J Chen, L Chen, S Jha
International Conference on Machine Learning, 5334-5342, 2018
272018
The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning
Z Shi, J Chen, K Li, J Raghuram, X Wu, Y Liang, S Jha
arXiv preprint arXiv:2303.00106, 2023
202023
Towards Evaluating the Robustness of Neural Networks Learned by Transduction
J Chen, X Wu, Y Guo, Y Liang, S Jha
arXiv preprint arXiv:2110.14735, 2021
172021
GRAPHITE: Generating Automatic Physical Examples for Machine-Learning Attacks on Computer Vision Systems
R Feng, N Mangaokar, J Chen, E Fernandes, S Jha, A Prakash
2022 IEEE 7th European Symposium on Security and Privacy (EuroS&P), 664-683, 2022
132022
ReabsNet: Detecting and Revising Adversarial Examples
J Chen, Z Meng, C Sun, W Tang, Y Zhu
arXiv preprint arXiv:1712.08250, 2017
132017
Revisiting adversarial robustness of classifiers with a reject option
J Chen, J Raghuram, J Choi, X Wu, Y Liang, S Jha
The AAAI-22 Workshop on Adversarial Machine Learning and Beyond, 2021
102021
Query-efficient physical hard-label attacks on deep learning visual classification
R Feng, J Chen, N Manohar, E Fernandes, S Jha, A Prakash
arXiv preprint arXiv:2002.07088, 2020
102020
Robust out-of-distribution detection via informative outlier mining
J Chen, Y Li, X Wu, Y Liang, S Jha
arXiv preprint arXiv:2006.15207 1 (2), 7, 2020
102020
Is forgetting less a good inductive bias for forward transfer?
J Chen, T Nguyen, D Gorur, A Chaudhry
arXiv preprint arXiv:2303.08207, 2023
92023
Representation Bayesian Risk Decompositions and Multi-Source Domain Adaptation
X Wu, Y Guo, J Chen, Y Liang, S Jha, P Chalasani
arXiv preprint arXiv:2004.10390, 2020
92020
Concept-based explanations for out-of-distribution detectors
J Choi, J Raghuram, R Feng, J Chen, S Jha, A Prakash
International Conference on Machine Learning, 5817-5837, 2023
82023
Toward Efficiently Evaluating the Robustness of Deep Neural Networks in IoT Systems: A GAN-Based Method
T Bai, J Zhao, J Zhu, S Han, J Chen, B Li, A Kot
IEEE Internet of Things Journal 9 (3), 1875-1884, 2021
72021
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs
J Chen, J Yoon, S Ebrahimi, SO Arik, T Pfister, S Jha
arXiv preprint arXiv:2310.11689, 2023
62023
The system can't perform the operation now. Try again later.
Articles 1–20