Neural implicit functions enable resolution-agnostic, deterministic virtual staining from H&E to IHC images with SOTA results and better low-data performance than patch-based GAN or diffusion methods.
Unifying diffusion models’ latent space, with applications to cyclediffusion and guidance
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
GenFocal uses probabilistic ML to downscale coarse climate projections to fine-scale weather events without paired training data and samples rare high-impact events more accurately than prior methods.
Three style-based neural architectures are proposed for real-time weather classification from images, with two truncated ResNet variants claimed to outperform prior methods and generalize across public datasets.
citing papers explorer
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Regional climate risk assessment from climate models using probabilistic machine learning
GenFocal uses probabilistic ML to downscale coarse climate projections to fine-scale weather events without paired training data and samples rare high-impact events more accurately than prior methods.