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Sparse pixel-level supervision can yield segmentation results on par with fully supervised methods, revolutionizing the efficiency of training deep learning models.
Neural ODEs aren't just for continuous-time dynamics anymore: this work shows they can unify and universally approximate both finite and infinite-dimensional operators, bridging the gap between NNs and neural operators.
