3 citations · 10 across the 27 of their papers we have counts for
5 papers · 1 filter
PICKLES: Covariance-Preconditioned Kinetic Langevin Ensemble Sampler
Hong Ye Tan, Stanley Osher, Yifan Chen
We propose a covariance-preconditioned kinetic Langevin ensemble sampler named PICKLES. This is a kinetic analogue of the affine invariant interacting Langevin dynamics (ALDI). PIC…
Vocabulary-size-independent Convergence of Discrete Diffusion Models: adjoint equations induce the right space
Kelvin Kan, Xingjian Li, Benjamin J. Zhang +3
Discrete diffusion has become a leading framework for generative modeling in various applications including language, vision, and biology. Existing convergence theory, however, exh…
Scalable Fixed-Point Framework for High-Dimensional Hamilton-Jacobi Equations
Yesom Park, Stanley Osher
We propose a novel, mesh-free, and gradient-free fixed-point approach for computing viscosity solutions of high-dimensional Hamilton-Jacobi (HJ) equations. By leveraging the Hopf-L…
SymPlex: A Structure-Aware Transformer for Symbolic PDE Solving
Yesom Park, Annie C. Lu, Shao-Ching Huang +3
We propose SymPlex, a reinforcement learning framework for discovering analytical symbolic solutions to partial differential equations (PDEs) without access to ground-truth express…
Accelerated Regularized Wasserstein Proximal Sampling Algorithms
Hong Ye Tan, Stanley Osher, Wuchen Li
We consider sampling from a Gibbs distribution by evolving a finite number of particles using a particular score estimator rather than Brownian motion. To accelerate the particles,…