Yifan Chen

Variational Optimality of Föllmer Processes and related design questions in generative diffusions [Slide]
Exploring High Dimensions in Dynamical Sampling: Flattening the Scaling Curve! [Slide]
Lipschitz Guided Dynamical Transport for generative flows of ill-conditioned distributions [Slide]
New Affine Invariant Ensemble Samplers and Their Dimensional Scaling [Slide]
Two topics in high dimensional sampling with applications in scientific computing [Slide]
Convergence of Unadjusted Langevin in High Dimensions: Delocalization of Bias [Slide]
Randomized and sparse Cholesky for learning with Gaussian processes [Slide]
Fast, Multimodal, Derivative-Free Bayes Inference with Fisher-Rao Gradient Flows [Slide]
Design of Gradient Flows for Sampling: Energy Functionals, Invariance, and Gaussian Approximation [Slide]
On Multiscale and Statistical Numerical Methods for PDEs and Inverse Problems [Slide]
Solving and Learning Nonlinear PDEs with Gaussian Processes [Slide]
Exponentially Convergent Multiscale Methods for solving elliptic and Helmholtz’s equation [Slide]
Developments of Multiscale and Probabilistic Methods for Solving PDEs and Inverse Problems [Slide]
Consistency of Hiearchical Parameter Learning: Empirical Bayesian and Kernel Flow Approaches [video1] [video2] [Slide]