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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,341 papers · 148 categories

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4795142189 · May 202619922001200920182026
48 results for continuum directions

A novel method for supervised dimension reduction using continuum directions.

problem Dimension reduction of multivariate data with auxiliary information.
method Minimizes a novel criterion to obtain continuum directions, bridging unsupervised to fully supervised methods.
result Sample continuum directions are inconsistent but have good classification performance.

The paper connects fluid mechanics, elasticity, and geometry to study wrinkled solutions.

problem Existence of wrinkled solutions in nonlinear partial differential equations.
method Develops connections between fluids, elasticity, and isometric embeddings, mapping mechanical equations into geometric frameworks.
result Geometric theory provides a method for addressing admissibility criteria in nonlinear conservation laws.

Smooth knots can be embedded into a specific Menger continuum.

problem Embedding smooth knots into a specific type of continuum.
method Explicit construction using cubical models and self-similarity of the Menger continuum.
result Every smooth knot can be isotoped into the Menger continuum.

We prove the following result announced in Todorov and Valov: Any homogeneous, metric ANRANR-continuum is a VGnV^n_G-continuum provided dimGX=n1\dim_GX=n\geq 1 and Hˇn(X;G)0\check{H}^n(X;G)\neq 0, where GG is a principal ideal domain. This implies that any homogeneous nn-dimensional metric ANRANR-continuum with $\check{H}^n(X;G)\neq…

2012-08-31abs ↗pdf ↗

New method converts video of dye plumes into PDEs for better understanding.

problem Inferring continuum models from uncalibrated video data.
method Develops a pipeline to convert grayscale recordings into scalar fields, isolates drift, and identifies transport laws.
result Selected reduced model outperforms advection-diffusion baselines and retains structural interpretability.

Generative model for morphological continuum of normal and pathological states.

problem Identifying trends and features that separate normality and pathology in biomedical images.
method Wasserstein Auto-encoder with HSIC regularization for latent features.
result Model generates a continuum of morphological changes corresponding to side information.

Continuum Dropout improves neural differential equations by preventing overfitting.

problem Overfitting in Neural Differential Equations (NDEs).
method Introduces Continuum Dropout, a regularization technique based on alternating renewal processes.
result Continuum Dropout outperforms existing methods in various tasks, improving generalization and uncertainty quantification.

Derives continuum model from discrete ε\varepsilon-graphs with connectivity functional.

problem Modeling diffusion in networks with varying connectivity.
method Energy-based continuum limit derivation, neural-network reconstruction of connectivity.
result Error between discrete and continuum energies is O(ε)O(\varepsilon), valid even with fluctuations.

Study transforms discrete graph surfaces into smooth continua through iterative subdivision.

problem Abstracting a smooth continuum from a discrete graph surface.
method Iterative Goldberg-Coxeter subdivision method to converge discrete surfaces into a continuum.
result The limit set forms a continuum geometric object from the discrete surface.

An important question that discrete approaches to quantum gravity must address is how continuum features of spacetime can be recovered from the discrete substructure. Here, we examine this question within the causal set approach to quantum gravity, where the substructure replacing the spacetime continuum is a locally f…

2006-04-28abs ↗pdf ↗

Generalizes Alexandroff's VnV^n-continua to cohomological dimensions.

problem Extending Alexandroff's concept of VnV^n-continua to cohomological dimensions.
method Proves that strongly locally homogeneous generalized continua with cohomological dimension nn are generalized VnV^n-spaces.
result Every strongly locally homogeneous continuum of covering dimension nn is a VnV^n-continuum in the sense of Alexandroff.

Proves continuum limits of Lipschitz learning using Γ-convergence.

problem Semi-supervised learning with graph-based methods and continuum limits of pp-Laplacian learning.
method Proves continuum limits of Lipschitz learning using Γ-convergence.
result Proves ΓΓ-convergence in the LL^\infty-topology to the supremum norm of the gradient.

This paper studies continuum-armed bandits under Besov smoothness conditions and derives minimax rates.

problem Optimizing an unknown function with limited evaluations.
method Studies continuum-armed bandits under Besov smoothness conditions and derives minimax rates.
result Minimax rates over Besov spaces are identical to those over the smallest Hölder space into which Besov spaces embed.

A mesh-free method solves continuum-marginal optimal transport problems.

problem Recovering minimum-energy velocity fields from time-continuous probability marginals.
method Embeds weak continuity equation in a reproducing kernel Hilbert space, optimizing with mini-batch stochastic methods.
result Accurately recovers drift and maintains marginal consistency in synthetic experiments.

Optimal reinsurance contracts designed for a continuum of risk types.

problem Designing optimal reinsurance contracts with a continuum of risk types.
method Principal-agent model, VaR at risk tolerance level, change of variables, univariate approach.
result Optimal reinsurance contracts are in stop-loss form, classifying agents into high and low risk groups.

This work proves the continuum limit of t-SNE for data visualization.

problem Understanding the theoretical basis of t-SNE from a continuum limit perspective.
method Proving the Kullback-Leibler divergence consistency as non o \infty for t-SNE.
result The continuum variational problem involving non-convex gradient regularization and penalty on probability density function magnitude.

We characterize those planar Peano continua that are homotopy equivalent to 1-dimensional sets. While many planar Peano continua are not homotopically 1-dimensional, we prove that each has fundamental group that embeds in the fundamental group of a 1-dimensional planar Peano continuum. We leave open the following quest…

2006-03-03abs ↗pdf ↗

We analyze directed, unweighted graphs obtained from xiRdx_i\in \mathbb{R}^d by connecting vertex ii to jj iff xixj<ε(xi)|x_i - x_j| < ε(x_i). Examples of such graphs include kk-nearest neighbor graphs, where ε(xi)ε(x_i) varies from point to point, and, arguably, many real world graphs such as co-purchasing graphs. We ask whethe…

2014-11-20abs ↗pdf ↗

Continuum transformers learn operators in context via gradient descent.

problem Generalizing transformers to handle infinite-dimensional inputs for in-context learning.
method Gradient descent in an operator RKHS, leveraging generalized representer theorems and gradient flows.
result Operator learned in context is Bayes Optimal Predictor in infinite depth limit.

Continuum-wise hyperbolicity is exactly the pseudo-Anosov dynamics with spine singularities.

problem Classification of continuum-wise hyperbolic surface homeomorphisms
method Proving a complete structural classification
result Every cwF_F-hyperbolic homeomorphism is pseudo-Anosov with spine singularities

We show how to associate an R-tree to the set of cut points of a continuum. If X is a continuum without cut points we show how to associate an R-tree to the set of cut pairs of X.

2009-05-15abs ↗pdf ↗

We analyze convergence of Fermat distances and their application in clustering.

problem Understanding convergence properties of Fermat distances on Riemannian manifolds.
method Geometric and statistical arguments in percolation theory, leveraging novel arguments for non-uniform densities and curved domains.
result Discrete, sample-based Fermat distances converge to their continuum analogues with a precise rate dependent on intrinsic dimensionality.

Unified algorithms for structured sparsity problems with optimal convergence rates.

problem Solving minimization problems with structured sparsity assumptions.
method Unified continuum of preconditioned forward-backward operator splitting algorithms and accelerated algorithms.
result The continuum of algorithms attains the theoretically optimal rate of convergence.

We introduce a concept of tree-graded metric space and we use it to show quasi-isometry invariance of certain classes of relatively hyperbolic groups, to obtain a characterization of relatively hyperbolic groups in terms of their asymptotic cones, to find geometric properties of Cayley graphs of relatively hyperbolic g…

2004-05-03abs ↗pdf ↗

Framework learns physics-informed continuum models from molecular data.

problem Discovering accurate and robust data-driven continuum models from molecular simulation data.
method Operator regression framework using neural networks in modal space with physical inductive biases.
result Learned operators generalize to unseen system characteristics.

We construct a functor AC(,)AC(-,-) from the category of path connected spaces XX with a base point xx to the category of simply connected spaces. The following are the main results of the paper: (i) If XX is a Peano continuum then AC(X,x)AC(X,x) is a cell-like Peano continuum; (ii) If XX is nn-dimensional then AC(X,x)AC(X, x)

2013-02-17abs ↗pdf ↗

Study of convergence of point-object configurations to a charged dust continuum.

problem Understanding the convergence of discretized point-object configurations to a charged dust continuum.
method Establishing existence and uniqueness of horizons/minimal surfaces, studying geometries of regions exterior to minimal surfaces, and discussing limits.
result Examples of scalar curvature jumps upon taking Gromov-Hausdorff and intrinsic flat limits.

Proposes a variational approach to shallow neural networks, bypassing optimization.

problem Theoretical understanding and optimization of shallow neural networks.
method Replaces discrete training with a continuum variational surrogate, proving global well-posedness and regularity.
result Optimal parameter density can be obtained by solving a single linear system, achieving O(1/N)O(1/N) generalization error.

Optimal strategy proposed for maximizing cumulative reward in continuum-armed bandits.

problem Maximizing cumulative reward in a scenario with limited resources and unknown stochastic rewards.
method Proposed an optimal strategy for a nonparametric setting with side information on actions.
result Optimal regret scales as \(O(T^{1/3})\) up to poly-logarithmic factors when \(T\) is proportional to \(N\).

We prove non-metricity in a continuum limit of randomly-distributed defects.

problem Emergence of non-metricity in continuum limit of point defects.
method Homogenization theorem applied to isotropically-distributed point defects modeled as a weighted Poisson point process.
result Non-metricity tensor emerges in the continuum limit of point defects.

We derive a continuum model from discrete elastic models on smooth manifolds.

problem Modeling stress-free configurations in geometrically-incompatible elastic systems.
method Variational convergence of discrete models to a continuum model.
result No stress-free configurations unless the manifold is flat.

We prove that every homomorphism from the fundamental group of a planar Peano continuum to the fundamental group of a planar or one-dimensional Peano continuum is induced by a continuous map up to conjugation. This is then used to provide a family of uncountable many planar Peano continua with pairwise non-isomorphic f…

2013-05-18abs ↗pdf ↗

Generalizes risk sharing models to a continuum of agents.

problem Risk sharing among a large number of heterogeneous agents.
method Modeling agents as points in a measure space, using risk measures on a probability space, and deriving dual representations.
result Explicit formulas for specific risk measures (entropic and expected shortfall) and applications to Pareto efficiency.