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.
Study of limits of Einstein-Bogomol'nyi metrics on P^1 in two regimes.
In this paper we construct new solutions of the Kahler-Yang-Mills equations, by applying dimensional reduction methods to the product of the complex projective line with a compact Riemann surface. The resulting equations, that we call gravitating vortex equations, describe Abelian vortices on the Riemann surface with b…
In this work we consider the gravitating vortex equations. These equations couple a metric over a compact Riemann surface with a hermitian metric over a holomorphic line bundle equipped with a fixed global section --- the Higgs field ---, and have a symplectic interpretation as moment-map equations. As a particular cas…
We obtain all possible solutions of a 1/4 Bogomol'nyi-Prasad-Sommerfield equation exactly, containing configurations made of walls, vortices and monopoles in the Higgs phase. We use supersymmetric U(N_C) gauge theories with eight supercharges with N_F fundamental hypermultiplets in the strong coupling limit. The moduli…
A new GAN loss function based on cumulant generating functions improves stability and robustness.
Existence and uniqueness of gravitating vortices on Riemann surfaces with specific properties.
The paper finds shape modes for vortices in a specific sigma model.
Solves existence of gravitating vortices with positive curvature.
We consider a general 4n-dimensional quaternionic Kahler geometry with a free action of the torus T^(n+1). The toric action lifts onto the Swann bundle of the quaternionic Kahler space to a tri-holomorphic action that commutes with the standard H* action on the bundle. By matching Pedersen and Poon's generalized Gibbon…
We present a systematic method to construct exactly all Bogomol'nyi-Prasad-Sommerfield (BPS) multi-wall solutions in supersymmetric (SUSY) U(N_C) gauge theories in five dimensions with N_F hypermultiplets in the fundamental representation for infinite gauge coupling. The moduli space of these non-Abelian walls is found…
A gas of Bogomol'nyi vortices in the Abelian Higgs model is studied on a compact Riemann surface of genus and area . The volume of the moduli space is computed and found to depend on and , but not on other details of the shape of the surface. The volume is then used to find the thermodynamic partit…
Gradient descent converges with arbitrary stepsize for separable data under Fenchel-Young losses.
The Bogomol'nyi-Prasad-Sommerfield (BPS) multi-wall solutions are constructed in supersymmetric U(N_C) gauge theories in five dimensions with N_F(>N_C) hypermultiplets in the fundamental representation. Exact solutions are obtained with full generic moduli for infinite gauge coupling and with partial moduli for finite …
This paper introduces a variational approximation framework using direct optimization of what is known as the {\it scale invariant Alpha-Beta divergence} (sAB divergence). This new objective encompasses most variational objectives that use the Kullback-Leibler, the R{é}nyi or the gamma divergences. It also gives access…
Paper introduces Lambda EVaR, a new risk measure.
The most fruitful approach to studying low energy soliton dynamics in field theories of Bogomol'nyi type is the geodesic approximation of Manton. In the case of vortices and monopoles, Stuart has obtained rigorous estimates of the errors in this approximation, and hence proved that it is valid in the low speed regime. …
Unified framework for network model assessment using maximum entropy.
The study explains YouTube commenters' behavior using rational inattention models.
A(DP)SGD improves federated learning privacy and efficiency.
This work optimizes induced correlation in joint graph embeddings.
In this paper we use wavelet concepts to show that correlation coefficient between two financial data's is not constant but varies with scale from high correlation value to strongly anti-correlation value This studies is important because correlation coefficient is used to quantify degree of independence between two va…
We analyze the daily stock data of the Nasdaq Composite index in the 22-year period 1992-2013 and identify market states as clusters of correlation matrices with similar correlation structures. We investigate the stability of the correlation structure of each state by estimating the statistical fluctuations of correlat…
This study uses local Gaussian correlation to analyze stock return tails, revealing more sensitive network properties.
The study uses DCC for financial market analysis, revealing hidden correlations.
Polynomial time algorithm matches correlated Gaussian matrices without vanishing correlation.
This paper treats the problem of screening for variables with high correlations in high dimensional data in which there can be many fewer samples than variables. We focus on threshold-based correlation screening methods for three related applications: screening for variables with large correlations within a single trea…
This paper introduces anti-correlation networks to study China's stock market.
The study shows how trade uncertainty affects stock-bond correlations over time.
Infinite CNNs lose spatial correlations, but can be restored by correlated weights.
We discuss some methods to quantitatively investigate the properties of correlation matrices. Correlation matrices play an important role in portfolio optimization and in several other quantitative descriptions of asset price dynamics in financial markets. Specifically, we discuss how to define and obtain hierarchical …
This research examines rare spurious correlations in neural networks and their impact on accuracy and privacy.
CVAEs improve VAEs by accounting for correlations in latent representations.
The study reveals how synaptic correlations promote dimension reduction in neural networks.
Proposes PSCCA for estimating correlations and canonical correlations in sparse count data.
Develops a theory of common decomposition for correlated Brownian motions.
Study examines NFT market dynamics using correlation and noise analysis.
Polynomial-time algorithm matches correlated random graphs with non-vanishing correlation.
Proposes a multi-view VAE for imputing missing data from correlated sources.
Neurons in the visual cortex are correlated in their variability. The presence of correlation impacts cortical processing because noise cannot be averaged out over many neurons. In an effort to understand the functional purpose of correlated variability, we implement and evaluate correlated noise models in deep convolu…
Enhances community detection in correlated networks with node attributes.
New method detects intrinsic cross-correlations in non-stationary time series affected by common factors.
Develops correlation number for specific potentials and Hitchin representations.
The study finds significant power-law cross correlations in Bitcoin's return-volatility dynamics.
Financial markets analyzed by reducing correlation matrix complexity.
We study power-law correlations properties of the Google search queries for Dow Jones Industrial Average (DJIA) component stocks. Examining the daily data of the searched terms with a combination of the rescaled range and rescaled variance tests together with the detrended fluctuation analysis, we show that the searche…
Discovering a correlation from one variable to another variable is of fundamental scientific and practical interest. While existing correlation measures are suitable for discovering average correlation, they fail to discover hidden or potential correlations. To bridge this gap, (i) we postulate a set of natural axioms …
This letter explores the behavior of conditional correlations among main cryptocurrencies, stock and bond indices, and gold, using a generalized DCC class model. From a portfolio management point of view, asset correlation is a key metric in order to construct efficient portfolios. We find that: (i) correlations among …
This paper analyzes correlations in patterns of trading of different members of the London Stock Exchange. The collection of strategies associated with a member institution is defined by the sequence of signs of net volume traded by that institution in hour intervals. Using several methods we show that there are signif…