A latent diffusion model over continuous implicit neural representations samples INR parameters from sparse keyframes to reconstruct plausible, smooth, and diverse motions while preserving keyframe accuracy.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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PILL-CoDe co-optimizes polypill geometry via supershapes and excipient maps via neural networks to match target drug-release curves using end-to-end differentiable modified Allen-Cahn and Fickian diffusion models.
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Generative Motion In-betweening by Diffusion over Continuous Implicit Representations
A latent diffusion model over continuous implicit neural representations samples INR parameters from sparse keyframes to reconstruct plausible, smooth, and diverse motions while preserving keyframe accuracy.
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PILL-CoDe: Inverse Design of Polypills via Automatic Differentiation for Prescribed Drug-Release Kinetics
PILL-CoDe co-optimizes polypill geometry via supershapes and excipient maps via neural networks to match target drug-release curves using end-to-end differentiable modified Allen-Cahn and Fickian diffusion models.