Despite the complicated formulation of DreamBooth and Diffusion-based text-to-image models, our methods effectively defend users from the malicious use of those models.
Furthermore, when analysing its asymptotic properties, SVGD reduces exactly to a single-objective optimization problem and can be viewed as a probabilistic version of this single-objective optimization problem.
This allows for precise comparisons between the Mondrian forest, the Mondrian kernel and the Laplace kernel in density estimation.
In this paper, we conducted an empirical study on BLEU score to (in)validate its suitability for the code migration task due to its inability to reflect the semantics of source code.
JSNeat follows a data-driven approach to recover names by searching for them in a large corpus of open-source JS code.