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.
Study explores geometric structure and prior for beta-logistic distribution.
We derive and approximate the conjugate prior of Dirichlet and beta distributions.
This paper studies the Fisher-Rao geometry on the parameter space of beta distributions. We derive the geodesic equations and the sectional curvature, and prove that it is negative. This leads to uniqueness for the Riemannian centroid in that space. We use this Riemannian structure to study canonical moments, an intrin…
New approach to Generalized Beta family using SDEs.
We describe the underlying probabilistic interpretation of alpha and beta divergences. We first show that beta divergences are inherently tied to Tweedie distributions, a particular type of exponential family, known as exponential dispersion models. Starting from the variance function of a Tweedie model, we outline how…
Beta-SOD detects and corrects noisy object re-identification using cosine similarity and Beta mixtures.
Paper introduces a new text clustering model using Beta-Liouville priors.
A beta function for double layers is defined and analyzed.
The Brylinski beta function is extended for coaxial layers on submanifolds.
Beta diffusion generates bounded data using multiplicative transitions.
This paper introduces a new market making approach using scaled beta distributions.
Proposes logistic-beta process for modeling dependent probabilities with beta marginals.
Study finds significant premium for low-beta stocks in firm-level idiosyncratic return distributions.
AI learns to classify and represent univariate distributions in a 2D latent space.
Efficiently models categorical data with low to medium class overlap, improving accuracy over standard distributions.
New model improves DNA methylation data analysis.
Bayesian Beta regression for proportions in high dimensions with theoretical guarantees.
Paper generalizes reward distribution in multi-armed bandits with temporally-partitioned rewards.
The paper uses geometric methods to classify medical data histograms.
In the present paper we study locally semiflat (we also call them semiintegrable) almost Grassmann structures. We establish necessary and sufficient conditions for an almost Grassmann structure to be alpha- or beta-semiintegrable. These conditions are expressed in terms of the fundamental tensors of almost Grassmann st…
New estimates show spectral gap stability in RCD spaces, close to Beta distribution.
Long Short-Term Memory (LSTM) infers the long term dependency through a cell state maintained by the input and the forget gate structures, which models a gate output as a value in [0,1] through a sigmoid function. However, due to the graduality of the sigmoid function, the sigmoid gate is not flexible in representing m…
The article explains the probabilistic method of default probability estimation by Pluto and Tasche.
We characterize the combinatorial structure of conditionally-i.i.d. sequences of negative binomial processes with a common beta process base measure. In Bayesian nonparametric applications, such processes have served as models for latent multisets of features underlying data. Analogously, random subsets arise from cond…
Beta process is the standard nonparametric Bayesian prior for latent factor model. In this paper, we derive a structured mean-field variational inference algorithm for a beta process non-negative matrix factorization (NMF) model with Poisson likelihood. Unlike the linear Gaussian model, which is well-studied in the non…
Study efficient algorithms for one-shot federated conformal prediction.
We model a closed economic system with interactions that generates the features of empirical wealth distribution across all wealth brackets, namely a Gibbsian trend in the lower and middle wealth range and a Pareto trend in the higher range, by simply limiting the an agents' interaction to only agents with nearly the s…
By a real alphabeta-geometry we mean a four-dimensional manifold M equipped with a neutral metric h such that (M,h) admits both an integrable distribution of alpha-planes and an integrable distribution of beta-planes. We obtain a local characterization of the metric when at least one of the distributions is parallel (i…
We propose a Monte Carlo simulation method to generate stress tests by VaR scenarios under Solvency II for dependent risks on the basis of observed data. This is of particular interest for the construction of Internal Models and requirements on evaluation processes formulated in the Commission Delegated Regulation. The…
Proposes a new factor to improve BAB strategies by recognizing bad-beta assets.
FDN improves probabilistic regressors' adaptability to distribution shifts.
Alternative model predicts health insurance reimbursement based on contract limitations.
This article analyzes the problem of estimating the time until an event occurs, also known as survival modeling. We observe through substantial experiments on large real-world datasets and use-cases that populations are largely heterogeneous. Sub-populations have different mean and variance in their survival rates requ…
We introduce the stochastic multiplicative point process modelling trading activity of financial markets. Such a model system exhibits power-law spectral density S(f) ~ 1/f**beta, scaled as power of frequency for various values of beta between 0.5 and 2. Furthermore, we analyze the relation between the power-law autoco…
Deep model learns complex latent codes without assuming factor structure.
New f-Betas for portfolio optimization using f-divergence risk measures.
This work improves distribution recovery from sparse data using Random Forest implicit regularization.
Study long-only minimum variance portfolio in one-factor market with arbitrary sign betas.
Study examines time-varying betas and their volatility in bank interest income and expense margins.
A new autoencoder method uses empirical beta copulas for generating data.
The complete part of the earthquake frequency-magnitude distribution (FMD), above completeness magnitude mc, is well described by the Gutenberg-Richter law. The parameter mc however varies in space due to the seismic network configuration, yielding a convoluted FMD shape below max(mc). This paper investigates the shape…
We argue that a stochastic model of economic exchange, whose steady-state distribution is a Generalized Beta Prime (also known as GB2), and some unique properties of the latter, are the reason for GB2's success in describing wealth/income distributions. We use housing sale prices as a proxy to wealth/income distributio…
Graph Beta Diffusion (GBD) generates graphs with mixed discrete and continuous components.
In this paper, an issue of building the RRC model using probability distributions other than beta distribution is addressed. More precisely, in this paper, we propose to build the RRR model using the truncated normal distribution. Heuristic procedures for expected value and the variance of the truncated-normal distribu…
With today's abundant streams of data, the only constant we can rely on is change. For stream classification algorithms, it is necessary to adapt to concept drift. This can be achieved by monitoring the model error, and triggering counter measures as changes occur. In this paper, we propose a drift detection mechanism …
Machine learning improves beta forecasts, enhancing equity valuation and portfolio performance.
The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. A gamma process is employed to model the rate measure of a Poisson process, whose normalization provides a random probability measure for mixture modeling and whose marginalization leads to an NB process f…
The area under the ROC curve is widely used as a measure of performance of classification rules. However, it has recently been shown that the measure is fundamentally incoherent, in the sense that it treats the relative severities of misclassifications differently when different classifiers are used. To overcome this, …