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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.

168,742 papers · 148 categories

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48 results for Digital tools

Digital tools may hinder or facilitate multidisciplinary collaboration in occupational health.

problem Challenges in multidisciplinary collaboration in occupational health.
method Study of a precursor SPSTI's digital tools and their impacts.
result Digital tools can act as both brakes and levers for multidisciplinary dynamics.

Several recent papers in digital topology have sought to obtain fixed point results by mimicking the use of tools from classical topology, such as complete metric spaces. We show that in many cases, researchers using these tools have derived conclusions that are incorrect, trivial, or limited.

2018-08-29abs ↗pdf ↗

Several recent papers in digital topology have sought to obtain fixed point results by mimicking the use of tools from classical topology, such as complete metric spaces and homotopy invariant fixed point theory. We show that in many cases, researchers using these tools have derived conclusions that are incorrect or tr…

2018-06-15abs ↗pdf ↗

Browsing and finding relevant information for Bangladeshi laws is a challenge faced by all law students and researchers in Bangladesh, and by citizens who want to learn about any legal procedure. Some law archives in Bangladesh are digitized, but lack proper tools to organize the data meaningfully. We present a text vi…

2017-11-14abs ↗pdf ↗

Study evaluates digital transformation impact on financial performance using LLMs.

problem Measuring and understanding the impact of digital transformation on financial performance.
method Constructed DT indicators from company reports; analyzed effects of different digital technologies.
result Digital transformation improves financial performance, but varies by technology.

The study uses Markov chains to forecast cryptocurrency market dynamics.

problem Forecasting and understanding market fluctuations in cryptocurrencies.
method Markov chains of orders one to eight were used to forecast intra-day returns of three major cryptocurrencies.
result Predictions from empirical probabilities outperform random choices.

This paper explores IT governance for CBDC adoption in financial markets.

problem Adopting CBDC requires new IT governance models in financial markets.
method Systematic Literature Review (SLR) of 14 studies on IT resources and governance models.
result Many IT resources and preliminary IT designs for CBDC governance identified.

The paper introduces new geometric methods to analyze radar electromagnetic wave statistics.

problem Analyzing spatio-temporal and polarimetric fluctuations of radar electromagnetic waves.
method Using statistical mechanics and Information Geometry, the paper defines a Fréchet barycentre and maximum entropy density for radar measurements.
result New tools for describing radar electromagnetic wave fluctuations, including a distance on covariance matrices.

Paper reviews neuromorphic engineering features and compares analog vs digital systems.

problem Lack of consensus and unclear features in neuromorphic engineering.
method Review of recent work, comparison of machine learning accelerator chips.
result Analog processing and reduced bit precision architectures offer best efficiencies.

Emergenet predicts animal influenza strain emergence, outperforming current methods.

problem Limited ability to quantitatively assess animal influenza strain emergence.
method Infer digital twin of sequence evolution using 220,151 HA sequences.
result Emergenet predictions outperform WHO seasonal vaccine recommendations and CDC IRAT scores.

Digital currencies exhibit multifractality due to heavy-tailed returns and temporal correlations.

problem Understanding market inefficiencies and predicting volatility in digital currencies.
method Multifractal cross-correlation analysis (MFCCA) and multifractal detrended fluctuation analysis (MFDFA).
result Temporal correlations are the primary source of multifractality in digital currency markets.

Automated digital twin discovery from biological data improves drug discovery and personalized medicine.

problem Developing reliable digital twins from noisy, incomplete biological data.
method Symbolic and sparse regression, Bayesian frameworks, deep learning, and large language models.
result Sparse regression generally outperforms symbolic regression, especially with Bayesian frameworks.

This paper uses LLMs to streamline industrial data-centric R&D cycles.

problem High costs in human, computational, and time resources in data-centric R&D.
method Explores how large language models can understand domain-specific requirements and automate R&D tasks.
result Promising results show potential for automating industrial data-centric R&D cycles.

This research assesses uncertainty quantification and sensitivity analysis for DTs in nuclear fuel performance.

problem Understanding the reliability and performance of advanced nuclear fuels using DTs.
method Introduces ML-based uncertainty quantification and sensitivity analysis methods applied to BISON fuel performance code.
result Demonstrates the effectiveness of DTs in multi-criteria decision-making for nuclear fuel performance.

Mathematical problems of digital terrain analysis include interpolation of digital elevation models (DEMs), DEM generalization and denoising, and computation of morphometric variables by calculation of partial derivatives of elevation. Traditionally, these procedures are based on numerical treatments of two-variable di…

2015-07-14abs ↗pdf ↗

This study synthesizes stablecoin systems and develops a performance evaluation framework.

problem Fragmented academic research on stablecoins across economics, law, and computer science.
method Multi-method research design including literature synthesis, performance evaluation framework, and case study.
result Unified taxonomy and performance evaluation framework for stablecoin design.

ISOMORPH creates a digital twin for supply chain logistics, advancing time-series forecasting benchmarks.

problem Lack of public benchmarks for supply chain logistics time-series forecasting.
method Developed a digital twin simulator with interpretable parameters and modular topology, generating datasets and verifying conservation laws.
result Foundation models achieve MASE values exceeding public benchmarks at low-to-moderate horizons, supporting UQ.

Digital twins improve single-arm trials by providing robust treatment effect estimates.

problem Lack of control arms in single-arm trials limits their gold-standard evidence.
method Outcome-model-based synthetic controls using machine learning models trained on historical data.
result Digital twins offer more robust treatment effect estimates and principled corrections.

This paper is the first attempt to formalize a new field of economics; studding the Intangibles Goods available on the Internet. We are taking advantage of the digital world's specific rules, in particular the zero marginal cost, to propose a theory of trading & sharing unified. A function based money is created as a w…

2014-05-07abs ↗pdf ↗

Deep learning is still not a very common tool in speaker verification field. We study deep convolutional neural network performance in the text-prompted speaker verification task. The prompted passphrase is segmented into word states - i.e. digits -to test each digit utterance separately. We train a single high-level f…

2018-03-13abs ↗pdf ↗

Detects AI-synthesized speech using cepstral and bispectral analysis.

problem Validating the authenticity of speech from AI-generated content.
method Integrates cepstral and bispectral analysis for distinguishing human from AI-synthesized speech.
result Higher-order statistics show less correlation for human speech compared to AI-synthesis, and cepstral analysis reveals unique power components.

The automatic digitizing of paper maps is a significant and challenging task for both academia and industry. As an important procedure of map digitizing, the semantic segmentation section mainly relies on manual visual interpretation with low efficiency. In this study, we select urban planning maps as a representative …

2018-09-28abs ↗pdf ↗

Paper presents a fast and adaptive filter for SI suppression in full-duplex transceivers.

problem Self-interference suppression in full-duplex transceivers with nonlinearity.
method Adaptive projected subgradient method (APSM) in a reproducing kernel Hilbert space (RKHS).
result The proposed method achieves favorable digital SIC performance compared to benchmarks.

In this paper, we show how to construct graph theoretical models of n-dimensional continuous objects and manifolds. These models retain topological properties of their continuous counterparts. An LCL collection of n-cells in Euclidean space is introduced and investigated. If an LCL collection of n-cells is a cover of a…

2017-05-02abs ↗pdf ↗

Incorrect fixed point assertions in digital topology are discussed.

problem Incorrect, incorrectly proven, or trivial fixed point assertions in digital topology.
method Continues earlier work on identifying and critiquing bad fixed point assertions.
result Clarifies the nature and extent of incorrect fixed point assertions in digital topology.

Gaussian processes (GPs) are versatile tools that have been successfully employed to solve nonlinear estimation problems in machine learning, but that are rarely used in signal processing. In this tutorial, we present GPs for regression as a natural nonlinear extension to optimal Wiener filtering. After establishing th…

2013-03-12abs ↗pdf ↗