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We propose DiffSRL, a dynamic state representation learning pipeline utilizing differentiable simulation that can embed complex dynamics models as part of the end-to-end training. ... However, current dynamic state representation learning methods scale poorly on complex dynamic systems such as deformable objects, and cannot directly embed well defined simulation function into the training ... To improve the performance of the state representation learning on deformable objects, we propose a new pipeline, DiffSRL, that utilizes a differentiable simulator to encode dynamic and constraint-related ...arXiv:2110.12352v2 fatcat:rtdu2v2nznf23alsgznc7vvw4e