Preprint

Optimal Sobolev Approximation by Deterministic and Random Shallow Sigmoidal Networks

Optimal Sobolev Approximation by Deterministic and Random Shallow Sigmoidal Networks. Preprint · Under review, 2026.

zhaohui-fu
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Moment-Informed Force Rescaling for Random-Batch Langevin Dynamics

Moment-Informed Force Rescaling for Random-Batch Langevin Dynamics. Preprint · Under review, 2026.

xingguo-wu
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Many-Body Coarse-Grained Molecular Dynamics with the Atomic Cluster Expansion

Many-Body Coarse-Grained Molecular Dynamics with the Atomic Cluster Expansion. Preprint, 2025.

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Yangshuai Wang
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Local Surrogates for Harmonic Vibrational Entropy in Multilattices

Local Surrogates for Harmonic Vibrational Entropy in Multilattices. Preprint · Under review, 2026.

tina-torabi
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Liquid Random Feature Methods for Time-Dependent Partial Differential Equations

Liquid Random Feature Methods for Time-Dependent Partial Differential Equations. Preprint · Under review, 2026.

jiale-linghu
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Geometry-Preserving Nudged Elastic Band and Dimer Methods under Anisotropic Force Uncertainty

Geometry-Preserving Nudged Elastic Band and Dimer Methods under Anisotropic Force Uncertainty. Preprint · Under review, 2026.

yifan-yu
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From Energy-Force Weighting to Primal-Dual Optimization of Machine-Learned Interatomic Potentials

From Energy-Force Weighting to Primal-Dual Optimization of Machine-Learned Interatomic Potentials. Preprint · Under review, 2026.

chenyu-wang
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Formulation and Analysis of Blended Atomistic to Higher-Order Continuum Coupling Methods for Crystalline Defects

Formulation and Analysis of Blended Atomistic to Higher-Order Continuum Coupling Methods for Crystalline Defects. Preprint, 2025.

junfeng-lu
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Analysis of Hessian Variance Scaling for Local and Global Cost Functions in Variational Quantum Algorithms

Analysis of Hessian Variance Scaling for Local and Global Cost Functions in Variational Quantum Algorithms. Preprint · Under review, 2026.

yihan-huang
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A Study on the Fine-Tuning Performance of Universal Machine-Learned Interatomic Potentials (U-MLIPs)

A Study on the Fine-Tuning Performance of Universal Machine-Learned Interatomic Potentials (U-MLIPs). Preprint, 2025.

xiaoqing-liu
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