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Xi Deng

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#artificial intelligence Preprint Sep 2026

PTNO: Training Neural Operators with Noisy Monte Carlo Estimates for Particle Transport Problems

Particle transport under multiple scattering is central to radiative transfer and plasma physics, yet high-fidelity Monte Carlo (MC) simulations must trace prohibitively many particles. Learning-based surrogates can amortize this cost, but typically train on expensive, well-converged MC solutions. We propose the Partic...

Yu-Bo Cao, Xi Deng, Meng-Qi Xia et al. · 0 citations
#machine learning Preprint Sep 2026

PosteriorBench: From Point Estimates to Posterior Matching in Evaluating Generative Inverse Solvers

Generative models are increasingly used to solve scientific inverse problems, but existing evaluations still focus primarily on whether a method can produce a single plausible reconstruction. This is insufficient for ill-posed problems, where multiple solutions may be consistent with the same sparse or noisy observatio...

Jia-Chen Yao, Zi-Siang Hsu, Xi Deng et al. · 0 citations

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