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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.

169,181 papers · 148 categories

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20395978 · May 202619922001200920182026
48 results for gamma divergence

Paper introduces a new variational objective using Alpha-Beta divergence.

problem Improving variational inference methods for complex distributions.
method Direct optimization of the sAB divergence with two control parameters.
result The sAB divergence framework provides a smooth interpolation and trade-offs between distribution properties.

Unified framework improves robust causal inference, overcoming Gaussian barriers and optimization issues.

problem Improving robust causal inference in non-Gaussian settings.
method Combines gamma-Divergence, GNC, and Gatekeeper mechanism.
result Enhanced robustness and global optimization in causal effect estimation.

We consider sequences of finitely generated discrete subgroups Gamma_i=rho_i(Gamma) of a rank 1 Lie group G, where the representations rho_i are not necessarily faithful. We show that, for algebraically convergent sequences (Gamma_i), unless Gamma_i's are (eventually) elementary or contain normal finite subgroups of ar…

2007-08-20abs ↗pdf ↗

The paper proves learning-curve monotonicity for maximum likelihood estimators in various parametric settings.

problem Establishing monotonicity guarantees for maximum likelihood estimators.
method Variants of GPT-5.2 Pro were used to derive the results.
result The paper proves monotonicity for maximum likelihood estimators in Gaussian and Gamma variables.

Develops information geometry for Lévy processes in finance.

problem Understanding the statistical properties of Lévy processes for financial modeling.
method Deriving α\alpha-divergences from Lévy triplets, identifying Fisher information matrix and α\alpha-connection.
result Identifies statistical implications and differential-geometric structures of Lévy processes.

The paper proposes a new method for updating neural network parameters using gradient conjugate priors.

problem Learning probability distributions of observed data using neural networks.
method Gradient conjugate prior (GCP) update for neural networks, connecting to log-likelihood maximization.
result The method differs from classical Bayesian updates, leading to different limiting behavior of prior parameters.

A nonpolycyclic nilpotent-by-cyclic group Gamma can be expressed as the HNN extension of a finitely-generated nilpotent group N. The first main result is that quasi-isometric nilpotent-by-cyclic groups are HNN extensions of quasi-isometric nilpotent groups. The nonsurjective injection defining such an extension induces…

2005-07-14abs ↗pdf ↗

Factor analysis improves PET image interpretation by considering non-standard noise distributions.

problem Improving interpretation of dynamic PET images with non-standard noise distributions.
method Proposes using β\beta-divergence to fit factor models for different noise distributions.
result Improves factor analysis results for various noise types in PET images.

Bayesian framework extracts features from high-dimensional spatio-temporal data.

problem Sparse structure and spatio-temporal dependence in high-dimensional data.
method Develops a Bayesian feature-extraction framework using Gaussian and Diffused-gamma priors, employing Bregman divergence likelihood and MCMC for posterior computation.
result Improves recovery of sparse features and enhances interpretability in the presence of spatio-temporal dependence.

Study analyzes Airbnb lead-time distributions for Nights Booked and Gross Booking Value, finding divergent shapes and tail behavior.

problem Analyzing lead-time distributions for Airbnb demand metrics.
method Compositional analysis of daily lead-time vectors, fitting Gamma, Weibull, and Lognormal distributions, using generalized Pareto for tail inference.
result Lead-time distributions for Nights Booked and Gross Booking Value diverge, with GBV concentrating more in mid-range horizons.

If Gamma is any finite graph, then the unlabelled configuration space of n points on Gamma, denoted UC^n(Gamma), is the space of n-element subsets of Gamma. The braid group of Gamma on n strands is the fundamental group of UC^n(Gamma). We apply a discrete version of Morse theory to these UC^n(Gamma), for any n and any …

2004-10-25abs ↗pdf ↗

Study on gamma-related OU processes with simulation methods.

problem Distributional properties and simulation of gamma-related OU processes.
method Investigation of gamma and bilateral gamma laws, derivation of closed-form densities and characteristic functions, and development of efficient simulation algorithms.
result Efficient algorithms for generating gamma-related OU processes with significantly faster performance than existing methods.

Let Gamma be a non-elementary Kleinian group acting on the closed n-dimensional unit ball and assume that its Poincare series converges at the exponent alpha. Let M_Gamma be the Gamma-quotient of the open unit ball. We consider certain families E = {E_1,...,E_p} of open subsets of M_Gamma such that M_Gamma minus the un…

2004-09-29abs ↗pdf ↗

We consider complex projective space P^{n} and a smooth closed curve gamma in P^{n}. Harvey and Lawson have defined the notion of the projective hull \hat{K} of a compact subset K in P^n. This concept is an analogue of the polynomial hull of compact subsets of C^{n}. In the present note we study the relation between th…

2008-07-23abs ↗pdf ↗

Develops a data augmentation method for models with gamma functions.

problem Models with gamma functions lack natural conjugate priors, complicating inference and prediction.
method Derives Pólya Inverse Gamma distributions and applies them to scalable EM and MCMC algorithms.
result Provides scalable algorithms for inference and prediction in models with gamma functions.

Mixture models with Gamma and or inverse-Gamma distributed mixture components are useful for medical image tissue segmentation or as post-hoc models for regression coefficients obtained from linear regression within a Generalised Linear Modeling framework (GLM), used in this case to separate stochastic (Gaussian) noise…

2016-07-26abs ↗pdf ↗

Let P be a locally finite circle packing in the plane invariant under a non-elementary Kleinian group Gamma and with finitely many Gamma-orbits. When Gamma is geometrically finite, we construct an explicit Borel measure on the plane which describes the asymptotic distribution of small circles in P, assuming that either…

2010-04-13abs ↗pdf ↗

We consider discrete subgroups Gamma of the simply connected Lie group SU~(1,1), the universal cover of SU(1,1), of finite level, i.e. the subgroup intersects the centre of SU~(1,1) in a subgroup of finite index, this index is called the level of the group. The Killing form induces a Lorentzian metric of constant curva…

2003-08-28abs ↗pdf ↗

New calibration methods improve fitting of weak variance-alpha-gamma process.

problem Improving fitting of a multivariate Lévy process.
method Comparison of three calibration methods: method of moments, maximum likelihood estimation, and digital moment estimation.
result Maximum likelihood estimation produces a better fit when a specific condition holds, while digital moment estimation produces a better fit when the condition is violated.

A quick gamma approximation speeds up Bayesian inference.

problem Inconvenient gamma shape parameter conjugate priors in Bayesian models.
method Introduced an easy algorithm to approximate gamma shape parameter full conditional by another gamma distribution.
result The approximation is accurate and fast, even for small sample sizes.

For i = 1,2, let Gamma_i be a lattice in a simply connected, solvable Lie group G_i, and let X_i be a connected Lie subgroup of G_i. The double cosets Gamma_igX_i provide a foliation F_i of the homogeneous space Gamma_i\G_i. Let f be a continuous map from Gamma_1\G_1 to Gamma_2\G_2 whose restriction to each leaf of F_1…

1998-02-10abs ↗pdf ↗

The article prices exchange options using variance gamma-like models.

problem Pricing exchange options under specific stochastic processes.
method Derives formulas for variance gamma and variance gamma++ processes, constructs multidimensional versions, calibrates parameters with real data.
result Closed formulas and numerical methods for evaluating exchange options.

Let Gamma be a finitely generated, amenable group. Using an idea of E Ghys, we prove that if Gamma has a nontrivial, orientation-preserving action on the real line, then Gamma has an infinite, cyclic quotient. (The converse is obvious.) This implies that if Gamma has a faithful action on the circle, then some finite-in…

2006-06-09abs ↗pdf ↗

The study examines how gamma positivity and PL homeomorphism types affect simplicial spheres.

problem Understanding gamma positivity and its relation to PL homeomorphism types in simplicial spheres.
method Using edge contractions and the link condition as proxies for flagness, the study analyzes the effect of gamma positivity on simplicial spheres.
result The link condition has a trivial effect on gamma vectors of high-dimensional simplicial spheres with nonnegative gamma vectors.

The group Gamma of automorphisms of the polynomial kappa(x,y,z) = x^2 + y^2 + z^2 - xyz -2 is isomorphic to PGL(2,Z) semi-direct product with (Z/2+Z/2). For t in R, Gamma-action on ktR = kappa^{-1}(t) intersect R displays rich and varied dynamics. The action of Gamma preserves a Poisson structure defining a Gamma-invar…

2003-05-06abs ↗pdf ↗

Given a properly embedded graph Gamma in a ball B and a punctured sphere Sigma properly embedded in B - Gamma, we examine the conditions on Gamma that are necessary to assure that Sigma is boundary parallel.

2000-05-19abs ↗pdf ↗

We say that a collection Gamma of geodesics in the hyperbolic plane H^2 is a modular pattern if Gamma is invariant under the modular group PSL_2(Z), if there are only finitely many PSL_2(Z)-equivalence classes of geodesics in Gamma, and if each geodesic in Gamma is stabilized by an infinite order subgroup of PSL_2(Z). …

2004-01-23abs ↗pdf ↗

Introduces a new Lévy process for modeling illiquid markets.

problem Modeling dynamic of assets in illiquid markets.
method Introduces Variance Gamma++ process, a new Lévy process, and provides efficient path simulation algorithms.
result Efficient pricing formula and parameter estimation for European options.

Modeling stock returns and volatility using a bivariate gamma generalized Laplace law.

problem Analyzing stock returns and volatility using a new statistical model.
method Maximum likelihood estimation for a bivariate generalized Laplace distribution, simplifying to linear regression.
result Explicit estimators derived with nonstandard convergence rates for certain parameter configurations.

The paper develops option pricing methods for bilateral Gamma stock models.

problem Developing accurate option pricing measures for bilateral Gamma stock models.
method Incorporates various mathematical techniques including Esscher transforms, minimal entropy martingale measures, and pp-optimal martingale measures.
result Illustrates the theory with a numerical example, providing practical application of the methods.

Develops a fast method for pricing American options under variance gamma model.

problem Inefficient methods for pricing American options under variance gamma model.
method Inspired by quadratic approximation method, uses machine learning on pre-calculated quantities to reduce error.
result Proposed method is efficient and accurate for practical use.