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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.

169,051 papers · 148 categories

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48 results for infinite series coefficients

New method constructs Morse-Novikov complex with infinite series coefficients.

problem Constructing Morse-Novikov complex with infinite series coefficients.
method Method involves constructing a Morse 1-form and pseudo-gradient, leading to a differential with infinite series coefficients.
result Differential of the Novikov complex has at least one infinite series coefficient.

Extends A-type coefficient polynomials to B-type setting, introducing new invariants.

problem Tackles the B-type skein relation and introduces new coefficient polynomials.
method Introduces coefficient polynomials associated with the B-type skein relation and proves their invariance under Reidemeister moves.
result Shows that the generating series of these coefficient polynomials recovers the Kauffman polynomial.

This paper conditions non-linear infinite-dimensional diffusion processes.

problem Conditioning non-linear and infinite-dimensional diffusion processes.
method Infinite-dimensional Girsanov's theorem to condition function-valued stochastic processes.
result Conditioning of non-linear infinite-dimensional diffusion processes is achieved.

Method learns latent SDEs from high-dimensional time series.

problem Learning latent stochastic differential equations from time series data.
method Self-supervised learning with variational autoencoders and Euler-Maruyama approximation.
result Can recover SDE coefficients and latent variables up to isometry with infinite data.

Aimed at geometric applications, we prove the homology cobordism invariance of the L2L^2-betti numbers and L2L^2-signature defects associated to the class of amenable groups lying in Strebel's class D(R)D(R), which includes some interesting infinite/finitenon-torsion-free groups. The proofs include the only prior known c…

2009-10-19abs ↗pdf ↗

New coefficient detects irrational rotation behavior on infinite-type surfaces.

problem Detecting irrational rotation behavior on surfaces of infinite type.
method Introducing a new quasimorphism, the Dehn twist coefficient, and proving its properties.
result The Dehn twist coefficient can have image all of R for some infinite-type surfaces.

New filling functions for groups with coefficients show different asymptotic behavior.

problem Difficulty in filling loops with surfaces in Cayley graphs.
method Defining homological filling functions with coefficients and proving their differences.
result Filling functions for nn-cycles with coefficients in different groups have distinct asymptotic behavior.

Project infinite time series graphs to finite marginal models using number theory.

problem Handling infinite time series graphs for causal inference.
method Projection method using number theory to find common ancestors in infinite graphs.
result Developed algorithm to project infinite graphs to finite marginal models.

Paper extracts features from time series to improve forecasting accuracy.

problem Forecasting time series generated by Itô-type processes with unknown coefficients.
method Statistical adjustment of mixture-type models to extract features from time series data.
result Additional statistical features enhance time series prediction accuracy.

New model forecasts long-memory series with time-varying parameters.

problem Forecasting long-memory series with dynamic parameters.
method Proposes a new long-memory model with a time-varying fractional parameter, driven by predictive likelihood score.
result Validated through Monte Carlo experiment and real data applications.

We define an infinite series of translation coverings of Veech's double-n-gon for odd n greater or equal to 5 which share the same Veech group. Additionally we give an infinite series of translation coverings with constant Veech group of a regular n-gon for even n greater or equal to 8. These families give rise to expl…

2010-05-25abs ↗pdf ↗

Study of linear classifiers in infinite imbalance scenarios.

problem Behavior of linear discriminant functions in extreme imbalance conditions.
method Analysis of linear classifiers under infinite imbalance, focusing on weight function properties and limit behavior.
result Limiting coefficient vectors reflect robustness or conservatism, optimizing against worst-case alternatives.

Neural GARCH models financial time series with time-varying coefficients.

problem Modeling conditional heteroskedasticity in financial time series.
method Neural network adaptation of GARCH and BEKK models with time-varying coefficients parameterized by a recurrent neural network.
result Neural Students t model consistently outperforms other models on financial time series.

The loop invariants of Dimofte-Garoufalidis is a formal power series with arithmetically interesting coefficients that conjecturally appears in the asymptotics of the Kashaev invariant of a knot to all orders in 1/N1/N. We develop methods implemented in SnapPy that compute the first 6 coefficients of the formal power se…

2015-03-09abs ↗pdf ↗

New algorithms predict causal links better than traditional methods in time series data.

problem Learning causal structure from time series data with challenges in real-world Earth sciences.
method Combination of established ideas for linear methods to identify causal links in non-linear systems, with a focus on large regression coefficients.
result Large regression coefficients can predict causal links better than small p-values in practice.

Lueck expressed the Gromov norm of a knot complement in terms of an infinite series that can be computed from a presentation of the fundamental group of the knot complement. In this note we show that Lueck's formula, applied to torus knots, yields surprising power series expansions for the logarithm function. This gene…

2006-11-01abs ↗pdf ↗

Develops methods for selecting and estimating smooth functional coefficients in high-dimensional multivariate functional data.

problem Functional predictor selection and estimation of smooth functional coefficients in high-dimensional multivariate functional data.
method Functional group-sparse regression methods in a generic Hilbert space of infinite dimension.
result Consistency of estimation and selection (oracle property) under infinite-dimensional Hilbert spaces.

This paper presents an infinite variational autoencoder (VAE) whose capacity adapts to suit the input data. This is achieved using a mixture model where the mixing coefficients are modeled by a Dirichlet process, allowing us to integrate over the coefficients when performing inference. Critically, this then allows us t…

2016-11-23abs ↗pdf ↗

Paper proposes forecast-necessity testing for accurate causal interpretation in nonlinear time-series models.

problem Misinterpretation of causal scores from nonlinear models as regression coefficients.
method Systematic edge ablation and forecast comparison to evaluate causal necessity.
result Causal relationships with similar scores can differ in their necessity for accurate prediction.

Our goal is to estimate causal interactions in multivariate time series. Using vector autoregressive (VAR) models, these can be defined based on non-vanishing coefficients belonging to respective time-lagged instances. As in most cases a parsimonious causality structure is assumed, a promising approach to causal discov…

2009-01-15abs ↗pdf ↗

We consider the asymptotic expansion of the heat kernel of a generalized Laplacian for t0+t\to 0^+ and characterize the coefficients aka_k of this expansion by a natural intertwining property. In particular we will give a closed formula for the infinite order jet of these coefficients on the diagonal in terms of the loc…

2001-05-17abs ↗pdf ↗

Hybridizes physical and data-driven methods for predicting physicochemical properties.

problem Predicting physicochemical properties accurately using limited data.
method Distills physical method predictions into a prior model and combines with sparse experimental data using Bayesian inference.
result Significant improvements in predicting activity coefficients at infinite dilution compared to baselines and ensemble methods.

Study optimal liquidation strategies with infinite horizon and regime switching.

problem Optimal liquidation with semimartingale strategies in a stochastic environment.
method Characterization of value function and optimal strategy via BSDEs with infinite horizon.
result Existence and uniqueness of optimal control problem solutions.

New method uses resurgent analysis to determine growth rate of quantum field theory coefficients.

problem Determining the growth rate of quantum field theory coefficients.
method Resurgence analysis on the Stokes line, leading to transseries decomposition and continued across natural boundary.
result Essential exponent of growth has Cardy-like interpretation as effective central charge.

New algorithm efficiently learns sparse causal graphs from time series data.

problem Learning sparse causal graphs from time series data efficiently and automatically selecting the number of edges.
method Cyclical coordinate descent algorithm with two non-parametric error metrics for LASSO coefficient selection.
result State-of-the-art performance on simulated and real datasets.