Vikash Sehwag
Princeton University(US)Sony Corporation (United States)(US)
Publications by Year
Research Areas
Adversarial Robustness in Machine Learning, Anomaly Detection Techniques and Applications, Advanced Neural Network Applications, Generative Adversarial Networks and Image Synthesis, Domain Adaptation and Few-Shot Learning
Most-Cited Works
- → RobustBench: a standardized adversarial robustness benchmark(2020)116 cited
- → Extracting Training Data from Diffusion Models(2023)96 cited
- → Analyzing the Robustness of Open-World Machine Learning(2019)57 cited
- → SSD: A Unified Framework for Self-Supervised Outlier Detection(2021)44 cited
- → Generating High Fidelity Data from Low-density Regions using Diffusion Models(2022)38 cited
- → PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking(2020)37 cited
- → HYDRA: Pruning Adversarially Robust Neural Networks(2020)31 cited
- → Robust Learning Meets Generative Models: Can Proxy Distributions Improve\n Adversarial Robustness?(2021)31 cited
- → Just Rotate it: Deploying Backdoor Attacks via Rotation Transformation(2022)30 cited
- → A Light Recipe to Train Robust Vision Transformers(2023)23 cited