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Open AccessDiscovering conservation laws using optimal transport and manifold learning
Conservation laws are key theoretical and practical tools for understanding, characterizing, and modeling nonlinear dynamical systems. However, for many complex systems, the corresponding conserved quantities ...
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Open AccessSurrogate- and invariance-boosted contrastive learning for data-scarce applications in science
Deep learning techniques have been increasingly applied to the natural sciences, e.g., for property prediction and optimization or material discovery. A fundamental ingredient of such approaches is the vast qu...
