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New tensor neural network tackles fractional PDEs with high accuracy

By PulseAugur Editorial · [3 sources] ·

Researchers have developed fTNN, a deterministic tensor neural network designed to solve fractional partial differential equations (PDEs). This method employs a geometry-adapted integration split and specialized quadrature techniques to handle the fractional Laplacian operator. The framework is particularly effective for problems with strong boundary singularities and long-time simulations, showing improved accuracy over existing fPINN and Monte Carlo baselines. AI

IMPACT Introduces a novel neural network architecture for solving complex mathematical problems, potentially advancing scientific computing.

RANK_REASON The cluster describes a new research paper detailing a novel method for solving fractional PDEs using a tensor neural network.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

New tensor neural network tackles fractional PDEs with high accuracy

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The cluster describes a new research paper detailing a novel method for solving fractional PDEs using a tensor neural network.
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COVERAGE [3]

  1. arXiv cs.LG TIER_1 English(EN) · Qingkui Ma, Hehu Xie, Xiaobo Yin ·

    fTNN: a tensor neural network for fractional PDEs

    arXiv:2606.27140v1 Announce Type: new Abstract: We develop the fTNN, a deterministic tensor neural network subspace method for problems involving the fractional Laplacian on bounded domains, taking the fractional Poisson equation and time-dependent fractional advection-diffusion …

  2. arXiv cs.LG TIER_1 English(EN) · Xiaobo Yin ·

    fTNN: a tensor neural network for fractional PDEs

    We develop the fTNN, a deterministic tensor neural network subspace method for problems involving the fractional Laplacian on bounded domains, taking the fractional Poisson equation and time-dependent fractional advection-diffusion equation as typical representatives. The work em…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    fTNN: a tensor neural network for fractional PDEs

    We develop the fTNN, a deterministic tensor neural network subspace method for problems involving the fractional Laplacian on bounded domains, taking the fractional Poisson equation and time-dependent fractional advection-diffusion equation as typical representatives. The work em…

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