RamanBench unifies 74 datasets into the first large-scale reproducible benchmark for ML on Raman spectra, finding tabular foundation models outperform baselines but no method generalizes across datasets.
Journal of Open Source Software5(48), 2173 (2020)
4 Pith papers cite this work, alongside 151 external citations. Polarity classification is still indexing.
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Semantic-aware random convolution and intensity-based source matching enable effective single-source domain generalization for medical image segmentation, outperforming prior methods and sometimes matching in-domain performance.
Introduces the A2A metric to evaluate propensity score matching methods by constructing artificial tasks with known outcomes, reducing ATE errors up to 50% when combined with SMD.
Graph metrics from similarity graphs plus active learning on cluster attributes produce a classifier that outperforms prior cluster repair methods on both clean and duplicate-containing datasets.
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RamanBench: A Large-Scale Benchmark for Machine Learning on Raman Spectroscopy
RamanBench unifies 74 datasets into the first large-scale reproducible benchmark for ML on Raman spectra, finding tabular foundation models outperform baselines but no method generalizes across datasets.
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Semantic-aware Random Convolution and Source Matching for Domain Generalization in Medical Image Segmentation
Semantic-aware random convolution and intensity-based source matching enable effective single-source domain generalization for medical image segmentation, outperforming prior methods and sometimes matching in-domain performance.
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Improving Bias Correction Standards by Quantifying its Effects on Treatment Outcomes
Introduces the A2A metric to evaluate propensity score matching methods by constructing artificial tasks with known outcomes, reducing ATE errors up to 50% when combined with SMD.
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Graph-based Active Learning for Entity Cluster Repair
Graph metrics from similarity graphs plus active learning on cluster attributes produce a classifier that outperforms prior cluster repair methods on both clean and duplicate-containing datasets.