Empirical measures from Kac's particle system converge to the Boltzmann equation solution for very soft potentials, proving propagation of chaos for all kernel classes.
Shiryaev.Limit Theorems for Stochastic Processes
8 Pith papers cite this work. Polarity classification is still indexing.
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A categorical framework characterizes robustness in program analysis as functors and gives recipes for lifting sound robust analyses from restricted models to general programs.
Mediated triangle transport yields graded interaction polynomials I_Σ^gr from conifold state data, extending binary support structures for BPS and stability theory.
Mixed-precision SSA with stochastic rounding preserves ensemble statistics across five biological models while cutting memory use by 2-4x and delivering up to 1.5x CPU speedup.
PCA is used to orthogonalize correlated auxiliary variables for constructing a more efficient estimator of the finite population mean under simple random sampling, with derived bias and MSE showing improved performance in simulations.
Quantum f-divergence equals classical f-divergence of Nussbaum-Szkoła distributions for normal states on semifinite von Neumann algebras.
A fixed-point neural operator framework models stochastic Fredholm integral equations as stochastic deep neural networks and applies them to financial equations including Black-Scholes, contagion dynamics, and Merton jump diffusion, with results reported to agree well.
Families of abelian varieties over curves in char p with small l-adic local systems have non-nef Hodge bundles and are non-liftable to W_2(k).
citing papers explorer
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Propagation of chaos for the Boltzmann equation with very soft potentials
Empirical measures from Kac's particle system converge to the Boltzmann equation solution for very soft potentials, proving propagation of chaos for all kernel classes.
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A Categorical Basis for Robust Program Analysis
A categorical framework characterizes robustness in program analysis as functors and gives recipes for lifting sound robust analyses from restricted models to general programs.
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From Finite-Node Conifold Geometry to BPS Structures III: Mediated Triangle Transport and Graded Interaction Data
Mediated triangle transport yields graded interaction polynomials I_Σ^gr from conifold state data, extending binary support structures for BPS and stability theory.
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Reduced-Precision Stochastic Simulation for Mathematical Biology
Mixed-precision SSA with stochastic rounding preserves ensemble statistics across five biological models while cutting memory use by 2-4x and delivering up to 1.5x CPU speedup.
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Principal Component Based Estimation of Finite Population Mean under Multicollinearity
PCA is used to orthogonalize correlated auxiliary variables for constructing a more efficient estimator of the finite population mean under simple random sampling, with derived bias and MSE showing improved performance in simulations.
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Quantum $f$-divergences via Nussbaum-Szko{\l}a Distributions in Semifinite von Neumann Algebras
Quantum f-divergence equals classical f-divergence of Nussbaum-Szkoła distributions for normal states on semifinite von Neumann algebras.
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Explainable Artificial Intelligence for Financial Integral Equations: A Fixed-Point Neural Operator Approach
A fixed-point neural operator framework models stochastic Fredholm integral equations as stochastic deep neural networks and applies them to financial equations including Black-Scholes, contagion dynamics, and Merton jump diffusion, with results reported to agree well.
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Non-liftability of Families of Abelian Varieties with Small $l$-adic Local System
Families of abelian varieties over curves in char p with small l-adic local systems have non-nef Hodge bundles and are non-liftable to W_2(k).