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Creators/Authors contains: "Khoo, Yuehaw"

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  1. ; ; (, Journal of Computational Physics)
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  2. ; ; (, Journal of Machine Learning Research)
    Accepted Manuscript Full Text Available
  3. ; ; (, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences)
    We propose an approach to directly estimate the moments or marginals for a high-dimensional equilibrium distribution in statistical mechanics by solving the high-dimensional Fokker–Planck equation in terms of low-order cluster moments or marginals. With this approach, we bypass the exponential complexity of estimating the full high-dimensional distribution and directly solve the simplified partial differential equations for low-order moments/marginals. Moreover, the proposed moment/marginal relaxation is fully convex and can be solved via off-the-shelf solvers. We further propose a time-dependent version of the convex programs to study non-equilibrium dynamics. In a specific setting, we show the proposed method can recover a mean-field-type equilibrium density. Numerical results are provided to demonstrate the performance of the proposed algorithm for high-dimensional systems. 
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  4. ; ; (, SIAM Journal on Scientific Computing)
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  5. ; ; (, Journal of Scientific Computing)
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  6. ; (, Journal of Computational Physics)
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  7. ; ; (, Journal of Computational and Applied Mathematics)
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  8. ; ; ; (, Research in the Mathematical Sciences)
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  9. ; ; ; ; (, Applied and Computational Harmonic Analysis)
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  10. ; ; (, SIAM Journal on Matrix Analysis and Applications)
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