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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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48 results for bijective transformations

This paper establishes that the Nahm transform sending spatially periodic instantons (instantons on the product of the real line and a three-torus) to singular monopoles on the dual three-torus is indeed a bijection as suggested by the heuristic. In the process, we show how the Nahm transform intertwines to a Fourier-M…

2017-12-14abs ↗pdf ↗

Cookbook transforms constrained statistical inference into unconstrained problems.

problem Transforming constrained statistical inference into unconstrained problems.
method Bijective and diffeomorphisms parametrizations.
result Maintains statistical inference properties like identifiability.

We systematically develop a transform of the Fourier-Mukai type for sheaves on symplectic manifolds XX of any dimension fibred in Lagrangian tori. One obtains a bijective correspondence between unitary local systems supported on Lagrangian submanifolds of XX and holomorphic vector bundles with compatible unitary conn…

2001-05-24abs ↗pdf ↗

Normalising flows (NFS) map two density functions via a differentiable bijection whose Jacobian determinant can be computed efficiently. Recently, as an alternative to hand-crafted bijections, Huang et al. (2018) proposed neural autoregressive flow (NAF) which is a universal approximator for density functions. Their fl…

2019-04-09abs ↗pdf ↗

Characterizes smiles in delta satisfying specific conditions.

problem Characterizing no butterfly arbitrage smiles in delta.
method Using parametrization of the smile in delta, we characterize the set of smiles.
result Obtained a parametrization of the set via one real number and three positive functions.

By the SYZ construction, a mirror pair (X,Xˇ)(X,\check{X}) of a complex torus XX and a mirror partner Xˇ\check{X} of the complex torus XX is described as the special Lagrangian torus fibrations XBX \rightarrow B and XˇB\check{X} \rightarrow B on the same base space BB. Then, by the SYZ transform, we can construct a simpl…

2019-05-02abs ↗pdf ↗

A new method for discrete data normalizing flows using latent transformations.

problem Challenges in parameterizing bijective transformations for discrete data.
method Predict a distribution over latent transformations to make the marginal likelihood differentiable.
result Discrete-data normalizing flows can be trained using gradient-based learning with unbiased score function estimation.

We establish a Penrose-Ward transform yielding a bijection between holomorphic principal 2-bundles over a twistor space and non-Abelian self-dual tensor fields on six-dimensional flat space-time. Extending the twistor space to supertwistor space, we derive sets of manifestly N=(1,0) and N=(2,0) supersymmetric non-Abeli…

2012-05-14abs ↗pdf ↗

New framework for better mapping of surfaces onto ellipsoids.

problem Mapping genus-0 closed surfaces onto spheres results in large distortion.
method Combining conformal and quasi-conformal mappings onto ellipsoids.
result Achieved a variety of ellipsoidal parameterizations with bijectivity.

Develops a framework for consistent loss functions with variable transformations.

problem Lack of theoretical understanding of variable transformations in consistent loss functions.
method Formal characterizations of consistency for transformed loss functions in two cases: realization and prediction variables.
result Establishes new identifiable and elicitable functionals for complex predictive tasks.

A bijection proves a polynomial volume for genus-0 hyperbolic surfaces with boundaries.

problem Proving the Weil-Petersson volume polynomial in boundary lengths for genus-0 surfaces.
method Generalizing a tree bijection to handle geodesic boundaries, extending spine construction.
result Explicit formula for three-point function in Weil-Petersson random surfaces.

We identify causal models with unobserved confounding using bijective generation mechanisms.

problem Identifying causal relationships with unobserved confounders.
method Establish counterfactual identifiability for BGMs and propose a learning method.
result Learned BGMs enable efficient counterfactual estimation.

This is a review with examples concerning the concepts of affine (in particular, constant and linear) vector fields and fundamental vector fields on a manifold. The affine, linear and constant vector fields on a manifold are shown to be in a bijective correspondence with the fundamental vector fields on it of respectiv…

2006-02-01abs ↗pdf ↗

Improved ANN-based Monte Carlo simulation for Higgs decay events.

problem Accurate simulation of Higgs boson decay events.
method Monte Carlo simulation using an Artificial Neural Network (ANN) with improved training algorithm.
result The ANN simulation of Higgs decay is within 0.7% of the true value and achieves 26% unweighting efficiency.

Given a pair of number fields with isomorphic rings of adeles, we construct bijections between objects associated to the pair. For instance we construct an isomorphism of Brauer groups that commutes with restriction. We additionally construct bijections between central simple algebras, maximal orders, various Galois co…

2015-05-18abs ↗pdf ↗

Transformers mimic Bayesian reasoning in controlled settings, revealing geometric mechanisms.

problem Verifying if transformers perform Bayesian reasoning rigorously in natural data.
method Constructing Bayesian wind tunnels with known posteriors and proving memorization impossibility.
result Transformers achieve 10310^{-3}-10410^{-4} bit accuracy in Bayesian posteriors, while MLPs fail.

Lossless compression methods shorten the expected representation size of data without loss of information, using a statistical model. Flow-based models are attractive in this setting because they admit exact likelihood optimization, which is equivalent to minimizing the expected number of bits per message. However, con…

2019-05-17abs ↗pdf ↗

The classical Fundamental Theorem of Affine Geometry states that for n2n\geq 2, any bijection of nn-dimensional Euclidean space that maps lines to lines (as sets) is given by an affine map. We consider an analogous characterization of affine automorphisms for compact quotients, and establish it for tori: A bijection o…

2016-12-17abs ↗pdf ↗

Graphical normalizing flows use Bayesian networks to improve normalizing flows' interpretability and performance.

problem Improving the interpretability and performance of normalizing flows.
method Revisiting normalizing flows as probabilistic graphical models, proposing graphical normalizing flows with either prescribed or learnable graph structures.
result Graphical conditioners lead to competitive white box density estimators.

Let XX be a topological space and f:XXf:X\to X a bijection. Let C(X,f){\mathcal C}(X,f) be a set of integers such that an integer nn is an element of C(X,f){\mathcal C}(X,f) if and only if the bijection fn:XXf^n:X\to X is continuous. A subset SS of the set of integers Z{\mathbb Z} is said to be realizable if there is a topologi…

2013-10-07abs ↗pdf ↗

We introduce an equivalence relation, called stable equivalence, on knot diagrams and closed curves on surfaces. We give bijections between the set of abstract knots, the set of virtual knots, and the set of the stable equivalence classes of knot diagrams on surfaces. Using these bijections, we define concordance and l…

2000-08-16abs ↗pdf ↗

We classify the torsion pairs in a tube category and show that they are in bijection with maximal rigid objects in the extension of the tube category containing the Pruefer and adic modules. We show that the annulus geometric model for the tube category can be extended to the larger category and interpret torsion pairs…

2011-12-28abs ↗pdf ↗

New method models intensity functions on spheres using normalizing flows.

problem Modeling non-homogeneous Poisson process intensity functions on the sphere.
method Flexible bijective map using normalizing flows to transform intensity functions.
result Normalizing flows provide a flexible way to model intensity functions on spheres.

EMFs combine deep learning and probabilistic models for better density estimation.

problem Combining domain-specific knowledge with general-purpose deep learning.
method Alternating transformations with structured layers that embed domain-specific inductive biases.
result EMFs induce desirable properties like multimodality and hierarchical coupling.