SemiConLens is a visual analytics platform that uses correlation-aware imputation and linked views with uncertainty glyphs to support reliable discovery of 2D semiconductors from limited datasets.
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TriForces adds a model-agnostic three-stream architecture plus self-supervised objectives to atomistic GNNs, improving transfer performance on MatBench, QM9, and limited-data OMat24 without DFT labels.
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SemiConLens: Visual Analytics for 2D Semiconductor Discovery
SemiConLens is a visual analytics platform that uses correlation-aware imputation and linked views with uncertainty glyphs to support reliable discovery of 2D semiconductors from limited datasets.
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TriForces: Augmenting Atomistic GNNs for Transferable Representations
TriForces adds a model-agnostic three-stream architecture plus self-supervised objectives to atomistic GNNs, improving transfer performance on MatBench, QM9, and limited-data OMat24 without DFT labels.