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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.

168,742 papers · 148 categories

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12.5%25.0%37.5%50.0% · May 199419922001200920172026
48 results for Dirac trick

We show that the R/Z part of the analytically defined eta invariant of Atiyah-Patodi-Singer for a Dirac operator on an odd dimensional closed spin manifold can be expressed purely geometrically through a stable Chern-Simons current on a higher dimensional sphere. As a preliminary application, we discuss the relation wi…

2003-07-09abs ↗pdf ↗

In this paper we analytically study the problem of pricing an arithmetically averaged Asian option in the path integral formalism. By a trick about the Dirac delta function, the measure of the path integral is defined by an effective action functional whose potential term is an exponential function. This path integral …

2010-08-28abs ↗pdf ↗

The Gumbel-max trick and its extensions simplify sampling from categorical distributions in machine learning.

problem Sampling from categorical distributions with unnormalized probabilities.
method Extensions of the Gumbel-max trick for various applications.
result Simplified and efficient methods for sampling and gradient estimation.

A new gradient estimator for categorical distributions reduces bias and variance.

problem Intractability of gradients for categorical distributions in discrete latent variable models.
method CatLog-Derivative trick and IndeCateR gradient estimator.
result IndeCateR reduces bias and variance of gradients for categorical distributions.

The paper establishes distance estimates for manifolds with lower scalar curvature bounds.

problem Distance estimates on manifolds with lower scalar curvature bounds.
method Introduced a definition of relative index via a deformed Dirac operator trick and proved index coincidence with Callias operators.
result Proved short neck inequality and quantitative shielding result with positive scalar curvature.

Embolic volume of compact manifolds is defined in terms of Berger's embolic inequality. In this paper, we show a result of relating embolic volume to the first Betti number. The proof relies on Gromov's covering argument appeared in systolic geometry. Berger called this method covering trick. We exploit and present mor…

2019-11-02abs ↗pdf ↗

Expands Bredon's trick for applications in geometry and topology.

problem Local-to-global extension principles in geometric and topological contexts.
method Novel applications and frameworks for stratified pseudomanifolds, Ricci flow, and persistent homology.
result Establishes Bredon's trick as a unifying framework.

We observe that gradients computed via the reparameterization trick are in direct correspondence with solutions of the transport equation in the formalism of optimal transport. We use this perspective to compute (approximate) pathwise gradients for probability distributions not directly amenable to the reparameterizati…

2018-06-05abs ↗pdf ↗

We introduce a family of pairwise stochastic gradient estimators for gradients of expectations, which are related to the log-derivative trick, but involve pairwise interactions between samples. The simplest example of our new estimator, dubbed the fundamental trick estimator, is shown to arise from either a) introducin…

2019-01-31abs ↗pdf ↗

The Gumbel trick is a method to sample from a discrete probability distribution, or to estimate its normalizing partition function. The method relies on repeatedly applying a random perturbation to the distribution in a particular way, each time solving for the most likely configuration. We derive an entire family of r…

2017-06-13abs ↗pdf ↗

An online reinforcement learning algorithm is anytime if it does not need to know in advance the horizon T of the experiment. A well-known technique to obtain an anytime algorithm from any non-anytime algorithm is the "Doubling Trick". In the context of adversarial or stochastic multi-armed bandits, the performance of …

2018-03-19abs ↗pdf ↗

Inference in popular nonparametric Bayesian models typically relies on sampling or other approximations. This paper presents a general methodology for constructing novel tractable nonparametric Bayesian methods by applying the kernel trick to inference in a parametric Bayesian model. For example, Gaussian process regre…

2011-03-09abs ↗pdf ↗

The reparameterization trick has become one of the most useful tools in the field of variational inference. However, the reparameterization trick is based on the standardization transformation which restricts the scope of application of this method to distributions that have tractable inverse cumulative distribution fu…

2019-11-06abs ↗pdf ↗

Boltzmann machines (BMs) are appealing candidates for powerful priors in variational autoencoders (VAEs), as they are capable of capturing nontrivial and multi-modal distributions over discrete variables. However, non-differentiability of the discrete units prohibits using the reparameterization trick, essential for lo…

2018-05-18abs ↗pdf ↗

We discuss replica analytic continuation using several simple models in order to prove mathematically the validity of replica analysis, which is used in a wide range of fields related to large scale complex systems. While replica analysis consists of two analytical techniques, the replica trick (or replica analytic con…

2016-06-23abs ↗pdf ↗

We define two categories of Dirac manifolds, i.e. manifolds with complex Dirac structures. The first notion of maps I call \emph{Dirac maps}, and the category of Dirac manifolds is seen to contain the categories of Poisson and complex manifolds as full subcategories. The second notion, \emph{dual-Dirac maps}, defines a…

2007-12-17abs ↗pdf ↗

Introduces weak (p,k)(p,k)-Dirac structures in geometric settings.

problem Defining and analyzing new geometric structures.
method Introducing and studying weak (p,k)(p,k)-Dirac structures in TMΛpTMTM \oplus \Lambda^pT^*M.
result Weak (p,k)(p,k)-Dirac structures contain more information than (p,k)(p,k)-Lagrangian structures.

Introduces compatibility between Dirac structures and Nijenhuis tensors.

problem No specific problem stated; focuses on extending Poisson-Nijenhuis structures.
method Introduces compatibility between Dirac structures and (1,1)-tensor fields.
result Properties of Dirac-Nijenhuis structures studied, including connections and integrations.

Tricks adversarial attacks to target specific classes, improving classifier accuracy.

problem Recent adversarial defense approaches have failed to protect classifiers from untargeted attacks.
method Target Training defense tricks untargeted attacks into targeted attacks on designated classes, then derives the real class.
result 86.2% accuracy for CW-L2 (confidence=0) in CIFAR10, outperforming unsecured classifiers.

Given a Dirac subbundle and an isotropic subbundle of a Courant algebroid, we provide a canonical method to obtain a new Dirac subbundle. When the original Dirac subbundle is involutive (i.e., a Dirac structure) this construction has interesting applications, for instance to Dirac's theory of constraints and to the Mar…

2007-02-01abs ↗pdf ↗

We show that a suitable notion of Dirac-Jacobi structure on a generic line bundle LL, is provided by Dirac structures in the omni-Lie algebroid of LL. Dirac-Jacobi structures on line bundles generalize Wade's E1(M)\mathcal E^1 (M)-Dirac structures and unify generic (i.e.~non-necessarily coorientable) precontact distribu…

2015-02-18abs ↗pdf ↗

We introduce Dirac processes, using Dirac delta functions, for short-rate-type pricing of financial derivatives. Dirac processes add spikes to the existing building blocks of diffusions and jumps. Dirac processes are Generalized Processes, which have not been used directly before because the dollar value of non-Real nu…

2015-04-17abs ↗pdf ↗

We had previously defined the rho invariant ρspin(Y,E,H,g)ρ_{spin}(Y,E,H, g) for the twisted Dirac operator ̸HE\not\partial^E_H on a closed odd dimensional Riemannian spin manifold (Y,g)(Y, g), acting on sections of a flat hermitian vector bundle EE over YY, where H=ij+1H2j+1H = \sum i^{j+1} H_{2j+1} is an odd-degree differential form on $Y…

2013-09-23abs ↗pdf ↗