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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.

168,657 papers · 148 categories

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4590135180 · Jun 202019922001200920172026
48 results for Jacobian Mapping

The paper studies global invertibility of maps on Finsler manifolds.

problem Global invertibility of locally Lipschitz maps on Finsler manifolds.
method Introduces pseudo-Jacobian and studies its relations with local metric properties of the map.
result Conditions for a map to be globally invertible and covering.

Normalizing flows optimize Jacobian determinant for unique likelihood objective.

problem Optimizing normalizing flows for unique likelihood.
method Showed Jacobian determinant is unique for given distributions, leading to a unique global optimum. Used eigenvalues of auto-correlation matrix for explicit likelihood expression.
result Explicit expression of likelihood for flows, independent of neural network parameterization, with theoretical optimal value.

We extend the well-known result that any fW1,n(Ω,Rn)f \in W^{1,n}(Ω,\mathbb{R}^n), ΩRnΩ\subset \mathbb{R}^n with strictly positive Jacobian is actually continuous: it is also true for fractional Sobolev spaces Ws,ns(Ω)W^{s,\frac{n}{s}}(Ω) for any snn+1s \geq \frac{n}{n+1}, where the sign condition on the Jacobian is understood in a distr…

2019-05-17abs ↗pdf ↗

In this note we survey recent results on the extrinsic geometry of the Jacobian locus inside Ag\mathsf{A}_g. We describe the second fundamental form of the Torelli map as a multiplication map, recall the relation between totally geodesic subvarieties and Hodge loci and survey various results related to totally geodesic…

2018-09-17abs ↗pdf ↗

The Jacobian of Douady-Earle extension equals 1 only for isometries.

problem Investigating the Jacobian of Douady-Earle extension maps.
method Analyzing the Jacobian of the Douady-Earle extension map and constructing sequences of hyperbolic surfaces.
result The Jacobian of the Douady-Earle extension map is 1 only when the map is an isometry, and it can grow arbitrarily large for certain sequences of surfaces.

JacNet learns Jacobians to enforce structure on derivatives for invertibility and Lipschitz functions.

problem Enforcing structure on derivatives of neural network mappings.
method Proposes using a neural network to directly learn the Jacobian of the input-output function, allowing control over derivative structure.
result Demonstrates learning invertible approximations to simple and 1-Lipschitz functions.

Efficiently regularizes deep learning models using Jacobian nuclear norm.

problem Regularizing deep learning models to prevent overfitting and improve generalization.
method Proposes a denoising-style approximation to penalize the Jacobian nuclear norm without computing the Jacobian matrix.
result Demonstrates that penalizing the average squared Frobenius norm of JgJg and JhJh is equivalent to penalizing the Jacobian nuclear norm for function compositions.

Develops analysis of Hölder continuous mappings on Heisenberg groups.

problem Analyzing Hölder continuous mappings on Heisenberg groups.
method Theory of distributional Jacobians and pullbacks of differential forms.
result Simple proof of a generalization of the Gromov non-embedding theorem and new results about Hölder homotopy groups.

Study on sphere-valued maps, proving energy convergence and current limits.

problem Understanding the behavior of sphere-valued Sobolev maps as their energy grows.
method Proving Gamma-convergence of pp-energies to the mass of an integral current.
result Jacobian convergence to an area-minimizing current in a cobordism class.

Study on fractional mass for codimension-two currents, proving equi-coercivity and Γ-convergence.

problem Defining and studying fractional mass for codimension-two currents on manifolds.
method Energy minimization with Jacobian constraint, equi-coercivity, Γ-convergence, weak linking.
result Equivalence of two formulations of fractional mass, improved regularity for ss-harmonic maps.

The Jacobian-based Saliency Map Attack is a family of adversarial attack methods for fooling classification models, such as deep neural networks for image classification tasks. By saturating a few pixels in a given image to their maximum or minimum values, JSMA can cause the model to misclassify the resulting adversari…

2018-08-23abs ↗pdf ↗

NODEs can approximate a wide range of diffeomorphisms with strong guarantees.

problem The approximation power of NODEs under certain conditions.
method Leveraging a structure theorem of the diffeomorphism group.
result NODEs can approximate a large class of diffeomorphisms with a stronger guarantee.

A new method speeds up training of deep models by avoiding Jacobian determinant computation.

problem Efficiently training deep neural networks with complex log-determinant terms.
method Relative gradients to compute Jacobian updates efficiently.
result Training neural networks with Jacobian log-determinant objectives becomes feasible.

Let Mg\mathcal M_g denote the moduli space of compact Riemann surfaces of genus gg and let Ag\mathcal A_g be the space of principally polarized abelian varieties of (complex) dimension gg. Let J:MgAgJ:\mathcal M_g\longrightarrow \mathcal A_g be the map which associates to a Riemann surface its Jacobian. The map JJ is in…

2008-11-25abs ↗pdf ↗

In this note, we prove a Schwarz-Pick type lemma for minimal maps between negatively curved Riemannian surfaces. More precisely, we prove that if f:MNf:M \to N is a minimal map with bounded Jacobian between two complete negatively curved Riemann surfaces M and N whose sectional curvatures σMσ_M and σNσ_N satisfy $infσ_M …

2019-03-31abs ↗pdf ↗

By results of the author there exists a projective (holomorphic) symplectic desingularization of the moduli space of rank-two torsion-free sheaves on a genus-two Jacobian with c1=0c_1=0 and c2=2c_2=2. This desingularization has a natural map to the self-product of the Jacobian. We show that the fiber over (0,0)(0,0) is a 6-di…

2000-10-19abs ↗pdf ↗

This study connects Jacobian regularization to adversarial robustness and improves generalization.

problem Adversarial attacks make deep neural networks vulnerable.
method Developed a connection between Jacobian regularization and adversarial training, and established robust generalization gaps.
result Jacobian norms are related to both standard and robust generalization.

OT-Flow uses optimal transport to improve CNFs for faster and more accurate density estimation.

problem Computational challenges in continuous normalizing flows.
method OT-Flow leverages optimal transport to regularize CNFs and uses exact trace computation.
result OT-Flow achieves competitive performance with one-fourth the number of weights and significant speedups.

Let GG a semisimple Lie group of non-compact type and let XG\mathcal{X}_G be the Riemannian symmetric space associated to it. Suppose XG\mathcal{X}_G has dimension nn and it has no factor isometric to either H2\mathbb{H}^2 or SL(3,R)/SO(3)\text{SL}(3,\mathbb{R})/\text{SO}(3). Given a closed nn-dimensional Riemannian manifold $…

2019-11-13abs ↗pdf ↗

On a closed symplectic surface Sigma of genus two or more, we give a new construction of an extended flux map (a crossed homomorphism from the symplectomorphism group Symp(Sigma) to the cohomology group H^1(Sigma;R) that extends the flux homomorphism). This construction uses the topology of the Jacobian of the surface …

2008-08-12abs ↗pdf ↗

This work proves the asymptotic freeness of layerwise Jacobians in MLPs with Haar orthogonal matrices.

problem Proving the asymptotic freeness of layerwise Jacobians in multilayer perceptrons (MLPs).
method Replacing each layer's parameter matrix with itself multiplied by a Haar orthogonal matrix, and using the invariance of the MLP.
result Proves the asymptotic freeness of layerwise Jacobians in MLPs with Haar orthogonal matrices.

Study shows a universal local obstruction to the Samuelson condition for tangent Lagrangian 2-webs.

problem Obstruction to the Samuelson condition for tangent Lagrangian 2-webs.
method Local analysis of tangent lines and their intersection maps.
result A universal local phenomenon produces a nonzero mixed derivative, obstructing the Samuelson condition.

New algorithm tackles optimization with distributed constraints.

problem Optimization problems with generalized orthogonality constraints in a decentralized setting.
method Introduced a novel algorithm that tracks gradients and Jacobians simultaneously.
result Global convergence with an iteration complexity established.

New findings on identifying latent variables in nonlinear ICA models.

problem Identifying latent variables in nonlinear ICA models is challenging due to spurious solutions.
method Proved that conformal maps are identifiable and provided theoretical results on preventing spurious solutions.
result Conformal maps are identifiable in nonlinear ICA models, preventing spurious solutions.

Paper tackles Hessian/Jacobian-free stochastic bilevel optimization with O(ε1.5){O}(ε^{-1.5}) complexity.

problem Nonconvex-strongly-convex bilevel optimization problem.
method FdeHBO optimizer with finite-difference Hessian/Jacobian-vector approximation and momentum.
result FdeHBO achieves O(ε1.5){O}(ε^{-1.5}) iterations for εε-accurate stationary point.

We show that codimension one dimensional Jacobian of the barycentric straightening map is uniformly bounded for most of the higher rank symmetric spaces. As a consequence, we prove that the locally finite simplicial volume of most Q\mathbb Q-rank 11 locally symmetric spaces is positive, which has been open for many y…

2015-03-09abs ↗pdf ↗

Recent work (Pennington et al, 2017) suggests that controlling the entire distribution of Jacobian singular values is an important design consideration in deep learning. Motivated by this, we study the distribution of singular values of the Jacobian of the generator in Generative Adversarial Networks (GANs). We find th…

2018-02-23abs ↗pdf ↗

We prove that affine invariant manifolds in strata of flat surfaces are algebraic varieties. The result is deduced from a generalization of a theorem of Möller. Namely, we prove that the image of a certain twisted Abel-Jacobi map lands in the torsion of a factor of the Jacobians. This statement can be viewed as a split…

2013-11-11abs ↗pdf ↗

The paper discusses fractional Sobolev immersions of flat domains into 3D space.

problem Developing C1C^1 regularity and isometric immersions of flat domains with fractional Sobolev regularity.
method Analysis of weak Codazzi-Mainardi equations, study of $W^{2, rac2s}$ planar deformations, and properties of the distributional Jacobian determinant.
result Generalization of isometric immersions with local fractional Sobolev regularity.

We derive an analytic formula for the dual Jacobian matrix of a generalised hyperbolic tetrahedron. Two cases are considered: a mildly truncated and a prism truncated tetrahedron. The Jacobian for the latter arises as an analytic continuation of the former, that falls in line with a similar behaviour of the correspondi…

2014-09-11abs ↗pdf ↗