activity
20152022
most citedParametric Reduced Models for the Nonlinear Schrödinger Equation

14 citations · 42 across the 12 of their papers we have counts for

collaborators

18 papers

quant-ph2022

Enabling Quantum Speedup of Markov Chains using a Multi-level Approach

Xiantao Li

Quantum speedup for mixing a Markov chain can be achieved based on the construction of slowly-varying Markov chains where the initial chain can be easily prepared and the spect…

cs.LG20222 cited

A Local Convergence Theory for the Stochastic Gradient Descent Method in Non-Convex Optimization With Non-isolated Local Minima

Taehee Ko, Xiantao Li

Loss functions with non-isolated minima have emerged in several machine learning problems, creating a gap between theory and practice. In this paper, we formulate a new type of loc…

quant-ph20214 cited

A Partially Random Trotter Algorithm for Quantum Hamiltonian Simulations

Shi Jin, Xiantao Li

Given the Hamiltonian, the evaluation of unitary operators has been at the heart of many quantum algorithms. Motivated by existing deterministic and random methods, we present a hy…

physics.comp-ph20211 cited

A Projection-based Reduced-order Method for Electron Transport Problems with Long-range Interactions

Weiqi Chu, Xiantao Li

Long-range interactions play a central role in electron transport. At the same time, they present a challenge for direct computer simulations, since sufficiently large portions of…

cs.LG20212 cited

Error Bounds of the Invariant Statistics in Machine Learning of Ergodic Itô Diffusions

He Zhang, John Harlim, Xiantao Li

This paper studies the theoretical underpinnings of machine learning of ergodic Itô diffusions. The objective is to understand the convergence properties of the invariant statistic…

math.NA2021

Projection based model reduction for the immersed boundary method

Yushuang Luo, Xiantao Li, Wenrui Hao

Fluid-structure interactions are central to many bio-molecular processes, and they impose a great challenge for computational and modeling methods. In this paper, we consider the i…