
Overparameterization of deep ResNet: zero loss and meanfield analysis
Finding parameters in a deep neural network (NN) that fit training data ...
read it

Constrained Ensemble Langevin Monte Carlo
The classical Langevin Monte Carlo method looks for i.i.d. samples from ...
read it

Random Coordinate Underdamped Langevin Monte Carlo
The Underdamped Langevin Monte Carlo (ULMC) is a popular Markov chain Mo...
read it

Random Coordinate Langevin Monte Carlo
Langevin Monte Carlo (LMC) is a popular Markov chain Monte Carlo samplin...
read it

Langevin Monte Carlo: random coordinate descent and variance reduction
Sampling from a logconcave distribution function on ℝ^d (with d≫ 1) is ...
read it

Variance reduction for Langevin Monte Carlo in high dimensional sampling problems
Sampling from a logconcave distribution function is one core problem th...
read it

Ensemble Kalman Inversion for nonlinear problems: weights, consistency, and variance bounds
Ensemble Kalman Inversion (EnKI), originally derived from Enseble Kalman...
read it

Ensemble Kalman Sampling: meanfield limit and convergence analysis
Ensemble Kalman sampling (EKS) is a method to find i.i.d. samples from a...
read it

Error Lower Bounds of Constant Stepsize Stochastic Gradient Descent
Stochastic Gradient Descent (SGD) plays a central role in modern machine...
read it

Meanfield limit and numerical analysis for Ensemble Kalman Inversion: linear setting
Ensemble Kalman inversion (EKI) is a method introduced in [14] to find s...
read it

Error analysis of an asymptotic preserving dynamical lowrank integrator for the multiscale radiative transfer equation
Dynamical lowrank algorithm are a class of numerical methods that compu...
read it
Zhiyan Ding
is this you? claim profile