The following pages link to DeepFool (Q32750):
Displaying 23 items.
- DiffRNN: differential verification of recurrent neural networks (Q832044) (← links)
- Analysis of classifiers' robustness to adversarial perturbations (Q1640392) (← links)
- Verification of piecewise deep neural networks: a star set approach with zonotope pre-filter (Q1982635) (← links)
- A survey of safety and trustworthiness of deep neural networks: verification, testing, adversarial attack and defence, and interpretability (Q2026298) (← links)
- Enhancing robustness verification for deep neural networks via symbolic propagation (Q2050096) (← links)
- MimicGAN: robust projection onto image manifolds with corruption mimicking (Q2056088) (← links)
- Quantized convolutional neural networks through the lens of partial differential equations (Q2079526) (← links)
- A robust generative classifier against transfer attacks based on variational auto-encoders (Q2123505) (← links)
- Black-box adversarial attacks by manipulating image attributes (Q2123528) (← links)
- Stronger data poisoning attacks break data sanitization defenses (Q2127214) (← links)
- Achieving adversarial robustness via sparsity (Q2127259) (← links)
- Scale-invariant scale-channel networks: deep networks that generalise to previously unseen scales (Q2163348) (← links)
- Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks (Q2193587) (← links)
- \textsc{Treant}: training evasion-aware decision trees (Q2212514) (← links)
- SyReNN: a tool for analyzing deep neural networks (Q2233513) (← links)
- Deep learning as optimal control problems: models and numerical methods (Q2297872) (← links)
- Compositional falsification of cyber-physical systems with machine learning components (Q2331078) (← links)
- Generating universal adversarial perturbation with ResNet (Q2666824) (← links)
- Adversarial classification via distributional robustness with Wasserstein ambiguity (Q2693647) (← links)
- The Gap between Theory and Practice in Function Approximation with Deep Neural Networks (Q4999396) (← links)
- Detecting Scene-Plausible Perceptible Backdoors in Trained DNNs Without Access to the Training Set (Q5004356) (← links)
- Active Subspace of Neural Networks: Structural Analysis and Universal Attacks (Q5037556) (← links)
- Achieving Adversarial Robustness Requires An Active Teacher (Q5079538) (← links)
