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D-JEPA: Design-Recoverable JEPA Representation with Swappable Physics Decoders
Joint-Embedding Predictive Architectures (JEPAs) provide a framework for learning compact representations without directly reconstructing high-dimensional observations. However, in parameterized physical systems, learned representations can entangle geometry with operating conditions and task-specif
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