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.

168,695 papers · 148 categories

Trend · papers per month

71141212282 · May 202619922001200920172026
48 results for log geometry

Study confirms boundedness of certain singularities in log Fano geometry.

problem Boundedness of log Fano cone singularities and minimal log discrepancies.
method Analyzing local volumes and minimal log discrepancies of Kollár components.
result Boundedness of K-semistable log Fano cone singularities confirmed in dimension three.

New insights from centro-affine geometry solve a key geometric conjecture.

problem Log-Brunn-Minkowski conjecture in centro-affine differential geometry.
method Interpreting the log-Brunn-Minkowski conjecture as a spectral problem and using centro-affine differential geometry.
result Global uniqueness and inequalities in the log-Minkowski problem for certain convex bodies.

Unified description of aesthetic curves through self-affinities.

problem Characterizing log-aesthetic curves and their properties.
method Reformulating and proving self-affinities of planar curves, integrating equiaffine geometry.
result Unified characterization of constant curvature curves in similarity and equiaffine geometries.

We develop a general theory of log spaces, in which one can make sense of the basic notions of logarithmic geometry, in the sense of Fontaine-Illusie-Kato. Many of our general constructions with log spaces are new, even in the algebraic setting. In the differentiable setting, our theory yields a framework for treating …

2015-07-24abs ↗pdf ↗

Using stable log maps, we introduce log twisted differentials extending the notion of abelian differentials to the Deligne-Mumford boundary of stable curves. The moduli stack of log twisted differentials provides a compactification of the strata of abelian differentials. The open strata can have up to three connected c…

2016-10-17abs ↗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.

This paper proves a curvature entropy inequality for non-symmetric convex bodies.

problem Proving a curvature entropy inequality for non-symmetric convex bodies.
method Demonstrated the log-Minkowski inequality of curvature entropy for general convex bodies in 2D.
result Equivalence of cone-volume measure uniqueness, log-Minkowski volume inequality, and curvature entropy inequality for general convex bodies in 2D.

A new dynamical formulation of log-PCA captures local principal modes of geodesic variations.

problem Learning principal variations of random probability measures under Wasserstein geometry.
method Introducing a new dynamical formulation of log-PCA as a variational approach.
result Deriving a general statistical convergence rate for empirical WT-PCA.

A new method compares unaligned datasets using log-Euclidean signatures of SPD matrices.

problem Efficiently comparing datasets with unknown alignment.
method Diffusion operators, Riemannian geometry, log-Euclidean metric.
result LES distance recovers meaningful structural differences, outperforming existing methods.

On a complete Riemannian manifold M with Ricci curvature satisfying Ric(r,r)Ar2(logr)2(log(logr))2...(logkr)2\textrm{Ric}(\nabla r,\nabla r) \geq -Ar^2(\log r)^2(\log(\log r))^2...(\log^{k}r)^2 for r1r\gg 1, where A>0 is a constant, and r is the distance from an arbitrarily fixed point in M. we prove some Liouville-type theorems for a C^2 function $f:M\ri…

2010-11-06abs ↗pdf ↗

New method computes affine normal directions efficiently for sparse polynomials.

problem Computing affine normal directions is computationally expensive in high dimensions.
method Reduces third-order tensor contraction to matrix-free formulation using log-determinant gradient.
result Scalable implementations with near-linear scaling in dimension and sparsity.

Proof of complex geometry theorem for specific singular spaces.

problem Proving a complex geometry theorem for a specific type of singular spaces.
method Self-contained proof of singular Beauville-Bogomolov decomposition theorem.
result Proof of singular Beauville-Bogomolov decomposition theorem for compact Kähler varieties with log terminal singularities and zero first Chern class.

Diffusion models adapt to data geometry through log-domain smoothing.

problem Understanding why diffusion models generalize well across diverse domains.
method Investigating the role of score matching and log-domain smoothing in diffusion models.
result Log-domain smoothing adapts the diffusion model to the data manifold.

The study finds effective lower bounds for spectra of random surfaces and bundles.

problem Determining the spectrum of Laplacian on random surfaces and bundles.
method Analysis of random covering surfaces and unitary bundles over finite-area non-compact hyperbolic surfaces.
result With high probability, the spectrum of random surfaces and bundles has no eigenvalues below a certain threshold.

Geometry-aware KDE model improves multiclass quantification.

problem Accurately estimating class prevalence for label shift adaptation.
method Log-ratio representations and Aitchison geometry for compositional data, shrinkage regularization.
result Competitive with state-of-the-art quantifiers, often improving over standard KDE-based baselines.

The paper extends localisation technique to multiple constraints in Euclidean spaces.

problem Proving log-concavity of conditional measures in decomposed convex sets.
method Defining partitions of maximal closed convex sets and proving log-concavity of conditional measures.
result Existence of a partition and log-concavity of conditional measures for almost every set of the partition.

The Milnor fiber conjecture is proven for splice type singularities.

problem Proving the Milnor fiber conjecture for a specific class of singularities.
method Combining techniques from tropical geometry, log geometry, and rounding of logarithmic spaces.
result The Milnor fiber conjecture is proven for splice type singularities.

Solves Tian's stabilization problem for toric Fano manifolds.

problem Tian's stabilization problem for equivariant global log canonical thresholds.
method Expressed complex singularity exponents in terms of support and gauge functions from convex geometry.
result First general result on Tian's problem.

We show that every coarse moduli space, parametrizing complex special linear rank two local systems with fixed boundary traces on a surface with nonempty boundary, is log Calabi-Yau in that it has a normal projective compactification with trivial log canonical divisor. We connect this to a novel symmetry of generating …

2016-12-08abs ↗pdf ↗

Study reveals how model volume affects learning curves in machine learning.

problem Understanding the double descent risk phenomenon in machine learning.
method Investigates the role of model volume using MDL, Occam's Razor, and information geometry.
result Model volume can explain the double descent risk, suggesting better generalization with increased dimensionality.

Unified framework for Riemannian deep learning across manifold-valued representations.

problem Deep learning on manifold-valued representations often relies on Euclidean approximations or costly geometric operations.
method Develops reusable neural modules, manifold-specific network architectures, and geometric designs.
result Generalizes batch normalization and multinomial logistic regression to broader classes of manifolds.

Study classifies gravitational instantons based on their asymptotic geometry.

problem Classifying gravitational instantons based on their asymptotic properties.
method Investigation of asymptotic geometry of Hermitian non-Kähler Ricci-flat metrics.
result All Hermitian non-Kähler gravitational instantons can be compactified to log del Pezzo surfaces.

The localization technique from convex geometry is generalized to the setting of Riemannian manifolds whose Ricci curvature is bounded from below. In a nutshell, our method is based on the following observation: When the Ricci curvature is non-negative, log-concave measures are obtained when conditioning the Riemannian…

2014-08-27abs ↗pdf ↗

Study geometric properties of log Calabi-Yau manifolds, focusing on Fano manifolds with smooth or two proportional components.

problem Geometric properties of log Calabi-Yau manifolds in two specific cases.
method Analysis of various geometric properties, focusing on Bochner principle, local triviality, polystability, and compactifiability of universal cover.
result The universal cover of XDX\setminus D is a Calabi-Yau manifold of infinite topological type when DD has two components.

A new geometry-preserving method for interpreting compositional data.

problem Statistical challenges in high-dimensional compositional data.
method Geometry-preserving framework for dimension reduction of compositional data.
result Identification of a central compositional subspace for compositional predictors.

Study the geometry of matrix multiplication in deep neural networks.

problem Understanding the structure of matrix multiplication in deep neural networks.
method Using quiver representations and equivariant cohomology, determine codimension and irreducible components.
result Codimension and number of top-dimensional irreducible components of matrix multiplication are invariant under permutations and have specific log-canonical thresholds.

Develops a functional generalization of Eldan's stochastic localization for optimization and privacy.

problem Sampling under non-Euclidean geometries and optimization in differential privacy.
method Functional generalization of Eldan's stochastic localization, incorporating log-Laplace transform.
result Improves query complexities in zeroth-order differential private convex optimization.