7 citations · 18 across the 6 of their papers we have counts for
7 papers
Deep JKO: time-implicit particle methods for general nonlinear gradient flows
Wonjun Lee, Li Wang, Wuchen Li
We develop novel neural network-based implicit particle methods to compute high-dimensional Wasserstein-type gradient flows with linear and nonlinear mobility functions. The main i…
Measuring Non-local Brane Order with Error-corrected Parity Snapshots
Junhyeok Hur, Wonjun Lee, Kiryang Kwon +3
Exotic quantum many-body states, such as Haldane and spin liquid phases, can exhibit remarkable features like fractional excitations and non-abelian statistics and offer new unders…
Derivation and Analysis of Simplified Filters for Complex Dynamical Systems
Wonjung Lee, Andrew Stuart
Filtering is concerned with the sequential estimation of the state, and uncertainties, of a Markovian system, given noisy observations. It is particularly difficult to achieve accu…
The adaptive patched cubature filter and its implementation
Wonjung Lee, Terry Lyons
There are numerous contexts where one wishes to describe the state of a randomly evolving system. Effective solutions combine models that quantify the underlying uncertainty with a…
Data Assimilation by Conditioning on Future Observations
Wonjung Lee, Chris Farmer
Conventional recursive filtering approaches, designed for quantifying the state of an evolving uncertain dynamical system with intermittent observations, use a sequence of (i) an u…
The adaptive patched particle filter and its implementation
Wonjung Lee, Terry Lyons
There are numerous contexts where one wishes to describe the state of a randomly evolving system. Effective solutions combine models that quantify the underlying uncertainty with a…
Kalman filtering and smoothing for linear wave equations with model error
Wonjung Lee, Damon McDougall, Andrew Stuart
Filtering is a widely used methodology for the incorporation of observed data into time-evolving systems. It provides an online approach to state estimation inverse problems when d…