CAP6412 21Spring-Introduction Lecture -1

(53:37)

CAP6412 21Spring-Explaining and harnessing adversarial examples

(27:6)

CAP6412 21Spring-Fast is better than free: Revisiting adversarial training

(33:58)

CAP6412 21Spring-Introduction Lecture -2

(1:8:52)

CAP6412 21Spring-Intriguing properties of neural networks

(29:25)

CAP6412 21Spring-How Can I Explain This to You? An Emp. Study of Deep Neural Net Explanation Methods

(36:46)

CAP6412 21Spring jan25

(20:9)

CAP6412 21Spring-Towards deep learning models resistant to adversarial attacks

(30:2)

CAP6412 21Spring-Smoothgrad: removing noise by adding noise

(28:19)

CAP6412 21Spring-Contrastive Learning with Adversarial Examples

(30:43)

CAP6412 21Spring-Adversarial Self-Supervised Contrastive Learning

(43:17)

CAP6412 21Spring-Universal adversarial perturbations

(23:20)

CAP6412 21Spring- Motion-Excited Sampler: Video Adversarial Attack with Sparked Prior

(24:6)

CAP6412 21Spring-Robust Pre-Training by Adversarial Contrastive Learning

(44:4)

CAP6412 21Spring- On adaptive attacks to adversarial example defenses

(24:54)

CAP6412 21Spring-Interpretable explanations of black boxes by meaningful perturbation

(27:24)

CAP6412 21Spring-Explainable AI: Interpreting, Explaining and Visualizing Deep Learning

(31:36)

CAP6412 21Spring-Improving transferability of adversarial examples with input diversity

(29:7)