FoReco and FoRecoML are R packages offering a unified framework for linear and non-linear forecast reconciliation in hierarchical time series.
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2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
nnU-Net segments rPCI regions on 62 CT scans with mean Dice 0.82, nearing inter-observer agreement of 0.88 and beating Swin UNETR at 0.76.
citing papers explorer
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FoReco and FoRecoML: A Unified Toolbox for Forecast Reconciliation in R
FoReco and FoRecoML are R packages offering a unified framework for linear and non-linear forecast reconciliation in hierarchical time series.
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Deep Learning-Based Segmentation of Peritoneal Cancer Index Regions from CT Imaging
nnU-Net segments rPCI regions on 62 CT scans with mean Dice 0.82, nearing inter-observer agreement of 0.88 and beating Swin UNETR at 0.76.