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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.

168,742 papers · 148 categories

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3517031,0541,405 · Jun 202019922001200920172026
48 results for discontinuous models

Cut-DeepONet handles discontinuities and sharp transitions in neural operators.

problem Neural operators struggle with discontinuities and sharp transitions in PDEs.
method Two-stage training framework that explicitly models discontinuities via a lifting strategy and input-dependent discontinuity prediction.
result Cut-DeepONet outperforms state-of-the-art methods on benchmark PDEs with low-resolution datasets.

Study proves existence of equilibrium in incomplete economies with discontinuous volatility.

problem Existence of incomplete Radner equilibrium with nondegenerate endogenous volatility.
method Established existence of solution for Markovian quadratic BSDEs with discontinuous generators using unique continuation and backward uniqueness.
result Existence of incomplete Radner equilibrium with nondegenerate endogenous volatility.

This work models overnight rates with jumps and discontinuities, extending classical short-rate models.

problem Capturing the jump behavior and discontinuities in overnight rates for accurate modeling.
method Developed a term structure modeling framework based on overnight rates, accommodating stochastic discontinuities.
result Simple specifications can capture the jump behavior of overnight rates, and explicit valuation formulas are provided.

Proves nonemptyness of domains for specific group actions.

problem Nonemptyness of domains of proper discontinuity for Anosov groups of affine Lorentzian transformations.
method Proof of nonemptyness of domains of proper discontinuity.
result Proves nonemptyness of domains for Anosov groups of affine Lorentzian transformations.

Quasi-experimental research designs, such as regression discontinuity and interrupted time series, allow for causal inference in the absence of a randomized controlled trial, at the cost of additional assumptions. In this paper, we provide a framework for discontinuity-based designs using Bayesian model comparison and …

2019-11-15abs ↗pdf ↗

This paper tackles discontinuous neural networks for better approximation of piecewise continuous functions.

problem Limitation of neural networks in approximating piecewise continuous functions due to discontinuities.
method Proposes a decoupled two-step procedure to train a discontinuous deep neural network model.
result Provides approximation guarantees for the proposed model in piecewise continuous function spaces.

Framework uses deep learning and statistical models to solve PDEs with discontinuous coefficients.

problem Solving PDEs with discontinuous coefficients.
method Two-stage physics-informed deep learning and statistical mixture models.
result Framework achieves adaptability and accurate parameter identification.

RLGP model improves robustness and accuracy for discontinuous response surfaces.

problem Challenges in modeling abrupt jumps and discontinuities in response surfaces.
method Integrates adaptive nearest-neighbor selection with robustification mechanism.
result Consistently delivers high predictive accuracy and robustness in higher dimensions.

We consider the deformation of a discontinuous group acting on the Euclidean space by affine transformations. A distinguished feature here is that even a `small' deformation of a discrete subgroup may destroy proper discontinuity of its action. In order to understand the local structure of the deformation space of disc…

2006-03-14abs ↗pdf ↗

Study proves rigid spectral properties of planets with metric discontinuities.

problem Establishing spectral rigidity for spherically symmetric planets with discontinuities.
method Novel trace formula applied to two wave types in spherically symmetric manifolds with boundary and interior interfaces.
result Spectral rigidity of spherically symmetric planets with discontinuities is proven.

Bayesian model estimates treatment effects near cutoffs in regression discontinuity designs.

problem Estimating conditional average treatment effects in regression discontinuity designs.
method Develops a Bayesian additive regression tree (BART) model with linear leaf-level regressions.
result Adapts to different slopes on the running variable near the cutoff, providing interpretable inference.

New domains of discontinuity found for Anosov representations.

problem Understanding Anosov representations acting on homogeneous spaces.
method Constructing open domains of discontinuity for Anosov representations acting on specific homogeneous spaces.
result Describes the largest possible open domains of discontinuity for Zariski dense Anosov representations.

The paper compares inserting and stretching points for grid refinement near critical points.

problem Decreased accuracy of finite difference methods near discontinuities.
method Comparison of inserting and stretching points for grid refinement near critical points.
result Proposes a new fast and simple stretching function.

We develop a method for quantile-based sensitivity analysis in models with discontinuities.

problem Uncertainty in interpreting discontinuous models using traditional derivatives.
method Quantile-based derivatives for discontinuous models with discrete inputs.
result Derivatives of quantile-based outputs are well-defined and provide meaningful insights.

Study new symmetries in non-symmetric spaces and discontinuous groups.

problem Analyze symmetries in non-symmetric homogeneous spaces and discontinuous groups.
method Investigate discrete series, discontinuous groups, and analysis on pseudo-Riemannian spaces.
result New insights into symmetries of non-symmetric homogeneous spaces and discontinuous groups.

Causal inference from observational data is hard due to discontinuous causal effects.

problem Causal inference from observational data is hard due to discontinuous causal effects.
method The problem is tackled by showing that many standard point estimates can be read as point summaries of multimodal distributions over the space of structural causal models.
result Many standard point estimates can be discontinuous summaries, while explicit posterior means and medians are continuous.

This article gives an up-to-date account of the theory of discrete group actions on non-Riemannian homogeneous spaces. As an introduction of the motifs of this article, we begin by reviewing the current knowledge of possible global forms of pseudo-Riemannian manifolds with constant curvatures, and discuss what kind of …

2006-03-14abs ↗pdf ↗

Paper analyzes error in stochastic approximation for discontinuous functions.

problem Estimating expected error in discontinuous stochastic approximation.
method Uses finite differences and O(n1/5)O(n^{-1/5}) error estimate for discontinuous functions.
result Achieves error estimate of O(n1/5)O(n^{-1/5}) for discontinuous stochastic representation.

Kolmogorov neural networks can represent various types of functions.

problem Representing different types of functions with neural networks.
method Continuous, discontinuous bounded or unbounded activation functions in a two hidden layer model.
result Kolmogorov neural networks can represent continuous, discontinuous bounded and all unbounded multivariate functions.

Selecting input variables or design points for statistical models has been of great interest in adaptive design and active learning. Motivated by two scientific examples, this paper presents a strategy of selecting the design points for a regression model when the underlying regression function is discontinuous. The fi…

2019-04-02abs ↗pdf ↗

The study explores deformations of discrete subgroups in non-compact homogeneous spaces.

problem Addressing the proper discontinuity of discrete subgroups in non-compact homogeneous spaces.
method Classification results for deformations of standard discontinuous groups in pseudo-Riemannian homogeneous spaces.
result Conditions for local rigidity and Zariski-dense deformations in standard quotients.

Paper analyzes SGHMC for non-convex optimization with discontinuous gradients.

problem Training neural networks with ReLU activation.
method Non-asymptotic convergence analysis of SGHMC with discontinuous gradients.
result Explicit upper bounds for expected excess risk in non-convex optimization.

In the framework of Lorentzian warped products, we study the Friedmann-Robertson-Walker cosmological model to investigate non-smooth curvatures associated with multiple discontinuities involved in the evolution of the universe. In particular we analyze non-smooth features of the spatially flat Friedmann-Robertson-Walke…

2003-08-16abs ↗pdf ↗

In this article we study properly discontinuous actions on Hilbert manifolds giving new examples of complete Hilbert manifolds with nonnegative, respectively nonpositive, sectional curvature with infinite fundamental group. We also get examples of complete infinite dimensional Kähler manifolds with positive holomorphic…

2013-09-16abs ↗pdf ↗

Estimates discontinuous optimal transport maps between a discrete and continuous distribution.

problem Estimating discontinuous optimal transport maps between a discrete and continuous distribution.
method Entropic optimal transport estimator, computationally efficient.
result The estimator converges at the minimax-optimal rate n1/2n^{-1/2} in the semi-discrete setting.

Study stability of selective SSMs with discontinuous gating.

problem Challenges in stability analysis of selective SSMs with discontinuous gating.
method Passivity and Input-to-State Stability (ISS) analysis of continuous-time selective SSMs.
result Derivation of sufficient conditions for global ISS with respect to the port input.

This work improves SGMs' convergence guarantees for semiconvex distributions with discontinuous gradients.

problem Establishing convergence guarantees for SGMs under weak regularity conditions.
method Developed non-asymptotic Wasserstein-2 convergence analysis for SGMs targeting semiconvex distributions with discontinuous gradients.
result Achieved optimal dependence of O(d)O(\sqrt{d}) on data dimension dd and convergence rate of order one.

Bayesian approach for estimating heterogeneous treatment effects in RDD designs.

problem Heterogeneity in treatment effects in RDD designs can lead to misleading conclusions.
method Direct Bayesian Additive Regression Trees (BART) for modeling heterogeneous treatment effects.
result Flexibly captures complicated structures of heterogeneous treatment effects as a function of covariates.

Motivated by the work of McCarthy and Papadopoulos for subgroups of mapping class groups, we construct domains of proper discontinuity in the compactified Outer space and in the projectivized space of geodesic currents for any "sufficiently large" subgroup of Out(FN)Out(F_N) (that is, a subgroup containing a hyperbolic iwip…

2009-02-25abs ↗pdf ↗