Search Results for author:
Found 4 papers, 1 papers with code
Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Models
To prove this result, we introduce a generic efficient watermark attack; the attacker is not required to know the private key of the scheme or even which scheme is used.
The Mori-Zwanzig formulation of deep learning
We develop a new formulation of deep learning based on the Mori-Zwanzig (MZ) formalism of irreversible statistical mechanics.
Improving neural network predictions of material properties with limited data using transfer learning
We develop new transfer learning algorithms to accelerate prediction of material properties from ab initio simulations based on density functional theory (DFT).
Density Propagation with Characteristics-based Deep Learning
Uncertainty propagation in nonlinear dynamic systems remains an outstanding problem in scientific computing and control.
