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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.

168,657 papers · 148 categories

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2 results for “graph-incorporation”

Graph-incorporated Latent Factor Analysis for High-dimensional and Sparse Matricescs.LG

GLFA improves latent factor analysis by incorporating graph structures for HiDS matrices.

problem Accurate representation learning on high-dimensional and sparse matrices.

method GLFA incorporates a graph to identify hidden high-order interactions and uses a recurrent LFA structure to improve representation learning.

result GLFA outperforms state-of-the-art models in predicting missing data of HiDS matrices.

latent factor analysis graph-incorporation high-dimensional sparse matrices representation learning high-order interactions

2022-04-16abs ↗pdf ↗

Bayesian Causal Inference with Gaussian Process Networksstat.ML

Bayesian method estimates intervention effects in non-linear data.

problem Causal discovery from observational data with non-linear relationships.

method Gaussian Process Networks (GPN) with Bayesian estimation and Monte Carlo methods.

result Approach accurately identifies and reflects uncertainty of causal estimates.

Bayesian inference Gaussian processes Causal discovery Non-linear data Intervention effects

2024-02-01abs ↗pdf ↗