A neural estimator trained on self-computed mutual information from masked diffusion model hidden states predicts the full pairwise MI matrix in one forward pass to enable faster parallel decoding of conditionally independent variables.
International Conference on Machine Learning , pages=
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cs.LG 2years
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UNVERDICTED 2representative citing papers
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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Neural Estimation of Pairwise Mutual Information in Masked Discrete Sequence Models
A neural estimator trained on self-computed mutual information from masked diffusion model hidden states predicts the full pairwise MI matrix in one forward pass to enable faster parallel decoding of conditionally independent variables.
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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.