CoDA aligns cross-domain latent reasoning representations in LLMs via CoT distillation and MMD to enable effective knowledge transfer without in-domain demonstrations.
Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
4 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 4representative citing papers
SPATE encodes data via spike trains mapped to quantum phases, yielding stronger feature representations than angle or amplitude encoding on datasets like Blobs and Moons.
K-means clustering on standard wireline logs identifies four electrofacies in the Keta Basin that track systematic changes in clay content, porosity, and rock framework from shale to cleaner sandstone.
Federated kMeans, PCA+kMeans, and LSH methods can approximate centralized clustering for molecular data diversity when evaluated with chemistry-informed metrics like the introduced SF-ICF.
citing papers explorer
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CoDA: Towards Effective Cross-domain Knowledge Transfer via CoT-guided Domain Adaptation
CoDA aligns cross-domain latent reasoning representations in LLMs via CoT distillation and MMD to enable effective knowledge transfer without in-domain demonstrations.
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SPATE: Spiking-Phase Adaptive Temporal Encoding for Quantum Machine Learning
SPATE encodes data via spike trains mapped to quantum phases, yielding stronger feature representations than angle or amplitude encoding on datasets like Blobs and Moons.
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Unsupervised Electrofacies Classification and Porosity Characterization in the Offshore Keta Basin Using Wireline Logs
K-means clustering on standard wireline logs identifies four electrofacies in the Keta Basin that track systematic changes in clay content, porosity, and rock framework from shale to cleaner sandstone.
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Insights into the Unknown: Federated Data Diversity Analysis on Molecular Data
Federated kMeans, PCA+kMeans, and LSH methods can approximate centralized clustering for molecular data diversity when evaluated with chemistry-informed metrics like the introduced SF-ICF.