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Found 5 papers, 5 papers with code
Mean-field underdamped Langevin dynamics and its spacetime discretization
We propose a new method called the N-particle underdamped Langevin algorithm for optimizing a special class of non-linear functionals defined over the space of probability measures.
Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm
This algorithm adds an accept-reject filter to the Markov chain induced by a single step of the Mirror Langevin algorithm (Zhang et al., 2020), which is a basic discretisation of the Mirror Langevin dynamics.
DiffusionWorldViewer: Exposing and Broadening the Worldview Reflected by Generative Text-to-Image Models
Generative text-to-image (TTI) models produce high-quality images from short textual descriptions and are widely used in academic and creative domains.
Approximate Cross-validation: Guarantees for Model Assessment and Selection
Cross-validation (CV) is a popular approach for assessing and selecting predictive models.
Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions
We also introduce a new first-order algorithm, called rescaled gradient descent (RGD), and show that RGD achieves a faster convergence rate than gradient descent provided the function is strongly smooth -- a natural generalization of the standard smoothness assumption on the objective function.
Optimization and Control
