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Showing 1 to 2 of 2 for “"physics priors"”.
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Large Scale Exact Gaussian Processes Inference and Euclidean Constrained Neural Networks with Physics Priors
Intelligent systems that interact with the physical world must be able to model the underlying dynamics accurately to be able to make informed actions and decisions. This requires accurate dynamics models that are scalable enough to learn from large amounts of data, robust enough to be used in the …
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Learning-Based Complex Terrain Navigation Under Uncertainty
… a unified framework to learn uncertainty-aware, physics-informed traversability models and achieve risk-aware navigation in both indistribution and out-of-distribution terrain. First, the proposed method efficiently quantifies both aleatoric and epistemic uncertainty by learning discrete …