Research
On-device research index

arXiv research

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

Trend · papers per month

25.0%50.0%75.0%100.0% · Dec 199319922001200920172026
48 results for semi-log canonical models

Compact Kahler-Einstein manifolds converge to semi-log canonical models.

problem Compactness of Kahler-Einstein manifolds of negative scalar curvature.
method Gromov-Hausdorff convergence and Weil-Petersson metric extension.
result Convergence to a finite union of complete Kahler-Einstein metric spaces.

We establish the existence of the K"ahler-Ricci flow on projective varieties with log canonical singularities. This generalizes some of the existence results of Song-Tian \cite{ST3} in case of projective varieties with klt singularities. We also prove that the normalized K"ahler-Ricci flow will converge to the \ka-Eins…

2019-06-11abs ↗pdf ↗

We give a formula of the Donaldson-Futaki invariants for certain type of semi test configurations, which essentially generalizes Ross-Thomas' slope theory. The positivity (resp. non-negativity) of those "a priori special" Donaldson-Futaki invariants implies K-stability (resp. K-semistability). We show its applicability…

2009-10-09abs ↗pdf ↗

Let XX be a canonically polarized variety, i.e. a complex projective variety such that its canonical class KXK_{X} defines an ample $\Q-$line bundle, and satisfying the conditions G1G_1 and S2S_2. Our main result says that XX admits a Kähler-Einstein metric iff XX has semi-log canonical singularities i.e. iff XX is…

2013-04-08abs ↗pdf ↗

Log minimality proven for weak K-moduli compactifications of Calabi-Yau varieties.

problem Constructing weak K-moduli compactifications of Calabi-Yau varieties.
method Revisiting classical problem, proving log minimality of normalizations under conditions.
result Log minimality of weak K-moduli compactifications under certain conditions.

Let π:XBπ: \mathcal{X}^* \rightarrow B^* be an algebraic family of compact Kähler manifolds of complex dimension nn with negative first Chern class over a punctured disc BCB^*\in \mathbb{C}. Let gtg_t be the unique Kähler-Einstein metric on Xt=π1(t)\mathcal{X}_t= π^{-1}(t). We show that as t0t\rightarrow 0, $(\mathcal{X}_t, g…

2017-06-05abs ↗pdf ↗

We show that the Kahler-Ricci flow on an algebraic manifold of positive Kodaira dimension and semi-ample canonical line bundle converges to a unique canonical metric on its canonical model. It is also shown that there exists a canonical measure of analytic Zariski decomposition on an algebraic manifold of positive Koda…

2008-02-19abs ↗pdf ↗

The existence of Kähler-Einstein metrics on a compact Kähler manifold has been the subject of intensive study over the last few decades, following Yau's solution to Calabi's conjecture. The Ricci flow, introduced by Richard Hamilton has become one of the most powerful tools in geometric analysis. We study the Kähler-Ri…

2006-02-08abs ↗pdf ↗

Constructs Kahler-Einstein metrics near isolated log canonical singularities.

problem Constructing metrics near singularities in complex geometry.
method Constructs Kahler-Einstein metrics with negative scalar curvature near isolated log canonical singularities.
result Metrics are complete near the singularity if the underlying space has complex dimension 2 or if the singularity is smoothable.

Canonical correlation analysis is a family of multivariate statistical methods for the analysis of paired sets of variables. Since its proposition, canonical correlation analysis has for instance been extended to extract relations between two sets of variables when the sample size is insufficient in relation to the dat…

2017-11-07abs ↗pdf ↗

D2PCCA integrates deep learning and probabilistic modeling for nonlinear dynamical systems.

problem Analyzing nonlinear dynamical systems with probabilistic understanding.
method Combines deep learning and probabilistic modeling, using KL annealing and normalizing flows.
result Captures latent dynamics in sequential datasets with improved convergence and flexibility.

Canonical transformation plays a fundamental role in simplifying and solving classical Hamiltonian systems. We construct flexible and powerful canonical transformations as generative models using symplectic neural networks. The model transforms physical variables towards a latent representation with an independent harm…

2019-09-30abs ↗pdf ↗

Paper proposes an alternative to MLE for GLMs with non-canonical link functions.

problem Challenges in MLE for GLMs with non-canonical link functions.
method Variational Inequality (VI) estimation framework.
result Established finite-sample error bounds and asymptotic normality for VI estimator.

Evaluation of the marginal likelihood plays an important role in model selection problems. The widely applicable Bayesian information criterion (WBIC) and singular Bayesian information criterion (sBIC) give approximations to the log marginal likelihood, which can be applied to both regular and singular models. When the…

2019-06-04abs ↗pdf ↗

New Hamiltonian Monte Carlo method for non-canonical dynamics.

problem Incompatibility of canonical symplectic structure with non-canonical dynamics.
method Developed a framework for Hamiltonian Monte Carlo using non-canonical symplectic structures with implicit integration.
result Non-canonical Hamiltonian Monte Carlo provides sampling advantages.

We study one parameter degenerations of complex projective manifolds by introducing certain type of Hodge metrics coming from the pluricanonical forms. We show that degenerations with at most canonical singularities are all in the finite distance boundary of moduli spaces. We also propose the converse to be true in the…

2002-11-29abs ↗pdf ↗

Defines plurisubharmonic metrics on hybrid spaces and proves their canonical extensions.

problem Defining and analyzing plurisubharmonic metrics on hybrid spaces.
method Introduces a class of plurisubharmonic metrics on hybrid spaces and proves their canonical extensions.
result Canonical plurisubharmonic extensions of metrics on hybrid spaces are continuous and can be described in terms of canonical models.

A new model for multiview data analysis using graph autoencoders.

problem Nonlinear multiview canonical correlation analysis for large datasets.
method Variational approach with graph convolutional neural networks.
result Competitive performance on classification, clustering, and recommendation tasks.

We study analytically and numerically Minority Games in which agents may invest in different assets (or markets), considering both the canonical and the grand-canonical versions. We find that the likelihood of agents trading in a given asset depends on the relative amount of information available in that market. More s…

2006-03-19abs ↗pdf ↗

The paper finds canonical triangulations for specific 3-manifolds.

problem Finding canonical decompositions for cusped hyperbolic 3-manifolds.
method Showed local convexity at every face of the geometric triangulation.
result Found canonical triangulations for Dehn fillings of the Borromean rings link complement and related manifolds.

Counterexample disproves log canonical Beauville--Bogomolov decomposition.

problem Disproving the log canonical Beauville--Bogomolov decomposition.
method Constructing a specific log canonical, K-trivial variety with non-birational fibers.
result Provides a counterexample to the Beauville--Bogomolov decomposition in the log canonical setting.

For a submanifold M in a Euclidean space, the tangential component x^T of the position vector field x of M is the most natural vector field tangent to the Euclidean submanifold, called the canonical vector field of M. In this article, first we prove that the canonical vector field of every Euclidean submanifold is alwa…

2018-01-22abs ↗pdf ↗

Canonical correlation analysis was proposed by Hotelling [6] and it measures linear relationship between two multidimensional variables. In high dimensional setting, the classical canonical correlation analysis breaks down. We propose a sparse canonical correlation analysis by adding l1 constraints on the canonical vec…

2017-05-30abs ↗pdf ↗

Paper proves structure of compact Kähler 3-folds with specific bundles.

problem Characterizing compact Kähler 3-folds with nef anti-canonical bundles.
method Minimal Model Program, positivity of direct image sheaves, Q-conic bundles, orbifold vector bundles.
result Compact Kähler 3-folds with nef anti-canonical bundles are essentially one of three types.

Self-regularizing RBMs learn optimal hidden units efficiently.

problem Learning optimal number of hidden units in RBMs.
method Grand-canonical extension of RBMs with varying hidden units, using chemical potential to control size.
result Efficiently deduces optimal number of hidden units with small generalization error.

Paper classifies compact symmetric triads using double Satake diagrams and canonical forms.

problem Classifying compact symmetric triads.
method Introducing double Satake diagrams and canonical forms, proving their existence and properties.
result Existence and properties of canonical forms for compact simple symmetric triads.

Proposes PSCCA for estimating correlations and canonical correlations in sparse count data.

problem Estimating correlations and canonical correlations in sparse count data from next-generation sequencing.
method Probabilistic approach for sparse count data sets (PSCCA).
result PSCCA outperforms other methods in estimating true correlations and canonical correlations at the natural parameter level.

The classical Beauville-Bogomolov Decomposition Theorem asserts that any compact Kähler manifold with numerically trivial canonical bundle admits an étale cover that decomposes into a product of a torus, and irreducible, simply-connected Calabi-Yau-- and holomorphic-symplectic manifolds. The decomposition of the simply…

2011-10-24abs ↗pdf ↗

To ensure interpretability of extracted sources in tensor decomposition, we introduce in this paper a dictionary-based tensor canonical polyadic decomposition which enforces one factor to belong exactly to a known dictionary. A new formulation of sparse coding is proposed which enables high dimensional tensors dictiona…

2017-04-03abs ↗pdf ↗