A plug-and-play bilateral breast gradient insert prototype achieves 2.8 mT/m/A efficiency and local strengths up to 1850 mT/m, allowing b=10000 s/mm² diffusion MRI at TE=78 ms versus 161 ms with scanner gradients.
Journal of Machine Learning Research , volume=
3 Pith papers cite this work. Polarity classification is still indexing.
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A physics-informed autoencoder compresses 3D charge density into a 16x16x16x16 latent representation that, combined with MAGPIE descriptors, predicts bulk modulus, Young's modulus, shear modulus, formation energy, and Debye temperature with R2 values of 0.94, 0.88, 0.87, 0.96, and 0.89 on 6059 DFT-s
Embeddings reliably capture authorial stylistic features in French literary texts, and these signals persist after LLM rewriting while showing model-specific patterns.
citing papers explorer
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Bilateral breast gradient insert prototype for strong diffusion encoding at 3T
A plug-and-play bilateral breast gradient insert prototype achieves 2.8 mT/m/A efficiency and local strengths up to 1850 mT/m, allowing b=10000 s/mm² diffusion MRI at TE=78 ms versus 161 ms with scanner gradients.
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Physics Aware Representation Learning on Electronic Charge Density for Materials Property Prediction
A physics-informed autoencoder compresses 3D charge density into a 16x16x16x16 latent representation that, combined with MAGPIE descriptors, predicts bulk modulus, Young's modulus, shear modulus, formation energy, and Debye temperature with R2 values of 0.94, 0.88, 0.87, 0.96, and 0.89 on 6059 DFT-s
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Measuring Embedding Sensitivity to Authorial Style in French: Comparing Literary Texts with Language Model Rewritings
Embeddings reliably capture authorial stylistic features in French literary texts, and these signals persist after LLM rewriting while showing model-specific patterns.