Establishes large deviation principle with speed n² for the normalized count of points in bounded set U for finite β-ensembles on R and C under suitable boundary conditions on U.
Billingsley.Convergence of probability measures
3 Pith papers cite this work. Polarity classification is still indexing.
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Models multi-head transformer data flow as time-dependent Wasserstein gradient flows of an attention-capturing interaction energy, with proofs on omega-limit stationary points and stability under weight and input perturbations.
Centered and scaled subgraph count vectors in the voter model on dynamic random graphs converge to a multidimensional Gaussian process as the number of vertices tends to infinity.
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Large deviations of crowding in finite $\beta$-ensembles
Establishes large deviation principle with speed n² for the normalized count of points in bounded set U for finite β-ensembles on R and C under suitable boundary conditions on U.
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Multi-Headed Transformer Architectures as Time-dependent Wasserstein Gradient Flows
Models multi-head transformer data flow as time-dependent Wasserstein gradient flows of an attention-capturing interaction energy, with proofs on omega-limit stationary points and stability under weight and input perturbations.
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Functional central limit theorem for the subgraph count of the voter model on dynamic random graphs
Centered and scaled subgraph count vectors in the voter model on dynamic random graphs converge to a multidimensional Gaussian process as the number of vertices tends to infinity.