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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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5 results for “mlr3”

mlr3torch: A Deep Learning Framework in R based on mlr3 and torchstat.ML

mlr3torch simplifies deep learning in R for tabular and image data.

problem Simplifying deep learning workflows in R for various data types.

method Built on torch, integrates mlr3 ecosystem, supports custom architectures.

result Extensible framework for tabular and image data, including preprocessing and model definition.

deep learning R torch mlr3 neural networks

2026-04-20abs ↗pdf ↗

mlr3spatiotempcv: Spatiotemporal resampling methods for machine learning in Rstat.ML

Package {mlr3spatiotempcv} simplifies spatiotemporal resampling methods in R.

problem Assessing and tuning spatial and spatiotemporal machine learning models.

method Integrates various spatiotemporal resampling methods into the {mlr3} framework.

result Provides a consistent interface for spatiotemporal resampling methods.

spatiotemporal resampling machine learning R package cross-validation model assessment

2021-10-25abs ↗pdf ↗

mlr3proba: An R Package for Machine Learning in Survival Analysisstat.CO

R package for machine learning in survival analysis.

problem Limited machine learning interfaces for survival analysis.

method Provides a comprehensive machine learning interface for survival analysis.

result Systematic infrastructure for survival modeling and evaluation.

machine learning survival analysis R package model tuning benchmarking

2020-08-18abs ↗pdf ↗

xtdml: Double Machine Learning Estimation to Static Panel Data Models with Fixed Effects in Recon.EM

R package xtdml uses DML for panel data models with fixed effects.

problem Estimating structural parameters in panel data models with fixed effects.

method Combines machine learning with statistical estimation for inference.

result Demonstrates improved performance in learning nuisance functions.

double machine learning panel data fixed effects R package structural estimation

2025-12-17abs ↗pdf ↗

DoubleML -- An Object-Oriented Implementation of Double Machine Learning in Rstat.ML

DoubleML implements machine learning for causal inference in R.

problem Estimating causal effects in regression models with high-dimensional data.

method Double machine learning framework with Neyman orthogonality and sample splitting.

result Valid inference on causal parameters using machine learning methods.

double machine learning causal inference R package machine learning sample splitting

2021-03-17abs ↗pdf ↗