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Injecting Hamiltonian Architectural Bias into Deep Graph Networks for Long-Range Propagation
The dynamics of information diffusion within graphs is a critical open issue that heavily influences graph representation learning, especially when considering long-range propagation.
MultiSTOP: Solving Functional Equations with Reinforcement Learning
We develop MultiSTOP, a Reinforcement Learning framework for solving functional equations in physics.
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