A cGAN-based inverse design framework generates 3D metamaterials with high local photon density of states via holographic lithography, outperforming the training dataset across a broad frequency range.
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UNVERDICTED 3representative citing papers
Soft Learning optimally combines heterogeneous ML specialists via cross-validated non-negative least squares, achieving top performance on 70% of 37 datasets with formal guarantees and 72-435x CPU speedups over deep networks.
SAM-derived models count plaques in virus titration plates with Pearson correlations of 0.92 and 0.88 to manual annotations on held-out data across viruses and plate formats.
citing papers explorer
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Photon density of states engineering with generative inverse design for scalable 3D photonic metamaterials
A cGAN-based inverse design framework generates 3D metamaterials with high local photon density of states via holographic lithography, outperforming the training dataset across a broad frequency range.
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Soft Learning
Soft Learning optimally combines heterogeneous ML specialists via cross-validated non-negative least squares, achieving top performance on 70% of 37 datasets with formal guarantees and 72-435x CPU speedups over deep networks.
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End-to-end plaque counting and virus titration from laboratory plate images with deep learning
SAM-derived models count plaques in virus titration plates with Pearson correlations of 0.92 and 0.88 to manual annotations on held-out data across viruses and plate formats.