Adversarial Attacks and Defenses. The Dimpled Manifold Hypothesis. David Stutz from DeepMind #HLF23

🎙️ Interview with David Stutz from Google DeepMind at the 10th HLF. We spoke about adversarial attacks and defenses for neural networks and about hypotheses that aim to explain their existence.

The HLF is an annual gathering of 200 young researchers from math and computer science and laureates of the most prestigious awards in these two fields, such as the ACM Turing Award, ACM Prize in Computing, Fields Medal, IMU Abacus Medal, Nevanlinna Prize (https://www.heidelberg-laureate-forum.org/laureates/awards.html).

I attended the last year’s …

adversarial adversarial attacks aim attacks david deepmind google google deepmind hypothesis interview manifold networks neural networks press researcher young