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.
New method clusters hydrological and sediment data for storm event analysis.
STORM enables edge computing for empirical risk minimization.
ST-STORM separates semantic and appearance features for robust representation learning.
STORM-PG uses momentum for faster policy gradient updates.
Improved neural network predicts tropical storm trajectories and Bayesian intervals.
We introduce a model-based reconstruction framework with deep learned (DL) and smoothness regularization on manifolds (STORM) priors to recover free breathing and ungated (FBU) cardiac MRI from highly undersampled measurements. The DL priors enable us to exploit the local correlations, while the STORM prior enables us …
Study examines stock price reactions to Texas winter storm power outages.
Study optimizes climate adaptation strategies for NYC.
Study examines equity in post-Snow Uri recovery, finds disparities.
Deep learning predicts tropical cyclone tracks efficiently.
Score matching method improves density estimation for truncated data on manifolds.
Kerckhoff and Storm conjectured that compact hyperbolic n-orbifolds with totally geodesic boundary are infinitesimally rigid when n>3. This paper verifies this conjecture for a specific example based on the 4-dimensional hyperbolic 120-cell.
FCNv2 robustness tested under noise and random initial conditions.
Improved sample complexity for actor-critic algorithms in MDPs.
Variance reduction has emerged in recent years as a strong competitor to stochastic gradient descent in non-convex problems, providing the first algorithms to improve upon the converge rate of stochastic gradient descent for finding first-order critical points. However, variance reduction techniques typically require c…
This paper is a follow-up to our joint paper with I. Agol, P. Storm and K. Whyte "Finiteness of arithmetic hyperbolic reflection groups". The main purpose is to investigate the effective side of the method developed there and its possible application to the problem of classification of arithmetic hyperbolic reflection …
Study character varieties of a Coxeter group in hyperbolic and Anti-de Sitter spaces.
New analysis identifies key factors in wildfire-generated thunderstorms.
Built the smallest non-commensurable hyperbolic 4-manifold.
Novel approach uses ENN for UQ in gust predictions, reducing RMSE and improving confidence.
Counterexamples found for volume entropy conjecture in hyperbolic 3-manifolds.
Study calibrated geometry in hyperkähler cones and their related spaces.
We prove that for any closed surface of genus at least four, and any punctured surface of genus at least two, the space of ending laminations is connected. A theorem of E. Klarreich implies that this space is homeomorphic to the Gromov boundary of the complex of curves. It follows that the boundary of the complex of cu…
Bitcoin treasury companies leverage stock to grow, using advanced statistical methods.
The Hessian of the renormalized volume of geometrically finite hyperbolic -manifolds without rank- cusps, computed at the hyperbolic metric with totally geodesic boundary of the convex core, is shown to be a strictly positive bilinear form on the tangent space to Teichmüller space. The metric is known fro…
We provide the first examples of geometric transition from hyperbolic to anti-de Sitter structures in dimension four, in a fashion similar to Danciger's three-dimensional examples. The main ingredient is a deformation of hyperbolic 4-polytopes, discovered by Kerckhoff and Storm, eventually collapsing to a 3-dimensional…
Nonparametric Bayesian approaches to clustering, information retrieval, language modeling and object recognition have recently shown great promise as a new paradigm for unsupervised data analysis. Most contributions have focused on the Dirichlet process mixture models or extensions thereof for which efficient Gibbs sam…
Pyrocast predicts pyrocumulonimbus clouds six hours before they form.
Predicting flood for any location at times of extreme storms is a longstanding problem that has utmost importance in emergency management. Conventional methods that aim to predict water levels in streams use advanced hydrological models still lack of giving accurate forecasts everywhere. This study aims to explore arti…
Following the previous work of Nikulin and Agol, Belolipetsky, Storm, and Whyte it is known that there exist only finitely many (totally real) number fields that can serve as fields of definition of arithmetic hyperbolic reflection groups. We prove a new bound on the degree of these fields in dimension 3: d…
Quantum method speeds up risk estimation for insurance tail risks.
We use self-report and electrodermal activity (EDA) wearable sensor data from 77 nights of sleep on six participants to test the efficacy of EDA data for sleep monitoring. We used factor analysis to find latent factors in the EDA data, and causal model search to find the most probable graphical model accounting for sel…
We survey recent work on the dynamics of the outer automorphism group of a word hyperbolic group on spaces of (conjugacy classes of) representations ofthe group into a semi-simple Lie group G. All these results are motivated by the fact that the mapping class group of a closed surface acts properly discontinuously on t…
Identifying anomalous patterns in real-world data is essential for understanding where, when, and how systems deviate from their expected dynamics. Yet methods that separately consider the anomalousness of each individual data point have low detection power for subtle, emerging irregularities. Additionally, recent dete…
2L-FUSE enhances feature sparsity through kernel learning.
AI helps forecasters understand TC convective evolution before intensification.
To a knot in 3-space, one can associate a sequence of Laurent polynomials, whose th term is the th colored Jones polynomial. The paper is concerned with the asymptotic behavior of the value of the th colored Jones polynomial at $e^{\a/n}$, when $\a$ is a fixed complex number and tends to infinity. We analy…
Big data trend has enforced the data-centric systems to have continuous fast data streams. In recent years, real-time analytics on stream data has formed into a new research field, which aims to answer queries about what-is-happening-now with a negligible delay. The real challenge with real-time stream data processing …
The study classifies weakly almost Fuchsian manifolds and proves geometric properties.
Paper proposes faster method to find local minima in nonconvex optimization.
This paper contains a purely topological theorem and a geometric application. The topological theorem states that if M is a simple closed orientable 3-manifold such that π_1(M) contains a genus g surface group and H_1(M;Z/2Z) has rank at least 4g-1 then M contains a closed incompressible surface of genus at most g. Thi…
NDI aims to forecast future natural disasters risk for insurers.
Given a knot in 3-space, one can associate a sequence of Laurrent polynomials, whose th term is the th colored Jones polynomial. The Generalized Volume Conjecture states that the value of the -th colored Jones polynomial at $\exp(2 πi \a/n)$ is a sequence of complex numbers that grows exponentially, for a fixe…
We introduce and study some deformations of complete finite-volume hyperbolic four-manifolds that may be interpreted as four-dimensional analogues of Thurston's hyperbolic Dehn filling. We construct in particular an analytic path of complete, finite-volume cone four-manifolds that interpolates between two hyperbo…
Standard supervised learning procedures are validated against a test set that is assumed to have come from the same distribution as the training data. However, in many problems, the test data may have come from a different distribution. We consider the case of having many labeled observations from one distribution, $P_…
Graph Attention Networks predict power outage durations from natural disasters.
Arctic coastal morphology is governed by multiple factors, many of which are affected by climatological changes. As the season length for shorefast ice decreases and temperatures warm permafrost soils, coastlines are more susceptible to erosion from storm waves. Such coastal erosion is a concern, since the majority of …
Robots hold promise in many scenarios involving outdoor use, such as search-and-rescue, wildlife management, and collecting data to improve environment, climate, and weather forecasting. However, autonomous navigation of outdoor trails remains a challenging problem. Recent work has sought to address this issue using de…