Adversarial Robustness in Machine Learning
Adversarial Robustness in Machine Learning is a topic indexed in PICO Portal from OpenAlex.
What is known about Adversarial Robustness in Machine Learning?
This cluster of papers focuses on the robustness of deep learning models against adversarial attacks, exploring topics such as adversarial examples, security, uncertainty estimation, defenses, and verification. It delves into the challenges and potential solutions for ensuring the resilience of neural networks in the face of malicious inputs.
How many works does Adversarial Robustness in Machine Learning have?
Adversarial Robustness in Machine Learning has 66,394 works in the PICO Portal index. The count is the OpenAlex total, not the number of papers listed on this page.
How many citations does Adversarial Robustness in Machine Learning have?
Adversarial Robustness in Machine Learning has 560,219 citations in the OpenAlex counts PICO Portal stores.
What is the OpenAlex record for Adversarial Robustness in Machine Learning?
The OpenAlex for Adversarial Robustness in Machine Learning is on the source record.