April 9, 2024, 4:42 a.m. | Diego Vallarino

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.04282v1 Announce Type: cross
Abstract: By integrating survival analysis, machine learning algorithms, and economic interpretation, this research examines the temporal dynamics associated with attaining a 5 percent rise in purchasing power parity-adjusted GDP per capita over a period of 120 months (2013-2022). A comparative investigation reveals that DeepSurv is proficient at capturing non-linear interactions, although standard models exhibit comparable performance under certain circumstances. The weight matrix evaluates the economic ramifications of vulnerabilities, risks, and capacities. In order to meet the …

abstract algorithms americas analysis arxiv convergence cs.lg dynamics econ.gn economic gdp interpretation investigation machine machine learning machine learning algorithms per power q-fin.ec q-fin.st research survival temporal type

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US

Research Engineer

@ Allora Labs | Remote

Ecosystem Manager

@ Allora Labs | Remote

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US