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Autor: Chen, Yian, Khoo, Yuehaw, Lim, Lek-Heng

We propose an approach to directly estimate the moments or marginals for a high-dimensional equilibrium distribution in statistical mechanics, via solving the high-dimensional Fokker-Planck equation in terms of low-order cluster moments or marginals.

Externí odkaz: http://arxiv.org/abs/2306.03292

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Combining Monte Carlo and Tensor-network Methods for Partial Differential Equations via Sketching

Autor: Chen, Yian, Khoo, Yuehaw

In this paper, we propose a general framework for solving high-dimensional partial differential equations with tensor networks. Our approach uses Monte-Carlo simulations to update the solution and re-estimates the new solution from samples as a tenso

Externí odkaz: http://arxiv.org/abs/2305.17884

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Generative Modeling via Hierarchical Tensor Sketching

Autor: Peng, Yifan, Chen, Yian, Stoudenmire, E. Miles, Khoo, Yuehaw

We propose a hierarchical tensor-network approach for approximating high-dimensional probability density via empirical distribution. This leverages randomized singular value decomposition (SVD) techniques and involves solving linear equations for ten

Externí odkaz: http://arxiv.org/abs/2304.05305

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Scalable Physics-based Maximum Likelihood Estimation using Hierarchical Matrices

Autor: Chen, Yian, Anitescu, Mihai

Physics-based covariance models provide a systematic way to construct covariance models that are consistent with the underlying physical laws in Gaussian process analysis. The unknown parameters in the covariance models can be estimated using maximum

Externí odkaz: http://arxiv.org/abs/2303.10102

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Akademický článek

High-Entropy Thermistor Ceramics (La 1/3 Nd 1/3 M 1/3) 2 (Zr 1/2 Sn 1/2) 2 O 7 (M = Sm, Eu, Gd, or Dy) with High Sensitivity for High-Temperature Measurements.

Autor: Chen, Yian^1,2 (AUTHOR) cacsz1999@126.com, Xuan, Tingting^1,2 (AUTHOR) xuantingting20@mails.ucas.ac.cn, Li, Xiaohui^1,2 (AUTHOR) lixiaohui@ms.xjb.ac.cn, Tuo, Yuling¹ (AUTHOR) tuoyl@ms.xjb.ac.cn, Chen, Xiaoyi^1,2 (AUTHOR) chenxiaoyi19@mails.ucas.ac.cn, Gao, Bo^1,2 (AUTHOR) chenxiaoyi19@mails.ucas.ac.cn

Publikováno v: Sensors (14248220). Dec2024, Vol. 24 Issue 23, p7523. 11p.