2 papers
math.NA2026
Convergence of the generalization error for deep gradient flow methods for PDEs
Chenguang Liu, Antonis Papapantoleon, Jasper Rou
The aim of this article is to provide a firm mathematical foundation for the application of deep gradient flow methods (DGFMs) for the solution of (high-dimensional) partial differ…
cs.LG2024
How to beat a Bayesian adversary
Zihan Ding, Kexin Jin, Jonas Latz +1
Deep neural networks and other modern machine learning models are often susceptible to adversarial attacks. Indeed, an adversary may often be able to change a model's prediction th…