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A conceptual demo from @poetengineer__ proposing a system where notes behave like force fields, allowing users to shape ideas through gestures and threading.
Introduces implicit machine learning force fields (I-MLFFs) that replace deep neural network stacks with fixed-point equations, enabling warm-starting and up to 5x compute/memory savings across graph neural network architectures for molecular dynamics simulations.
The paper introduces EquiFiLM, a lightweight extension that adds continuous external conditioning to equivariant foundation machine learning force fields via Feature-wise Linear Modulation, achieving significant accuracy improvements with minimal training data.