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Found 4 papers, 2 papers with code
Scattering with Neural Operators
Recent advances in machine learning establish the ability of certain neural-network architectures called neural operators to approximate maps between function spaces.
Coaction and double-copy properties of configuration-space integrals at genus zero
We investigate configuration-space integrals over punctured Riemann spheres from the viewpoint of the motivic Galois coaction and double-copy structures generalizing the Kawai-Lewellen-Tye (KLT) relations in string theory.
High Energy Physics - Theory Mathematical Physics Mathematical Physics Number Theory
Renormalization of tensor networks using graph independent local truncations
Together with a tensor network coarse-graining algorithm, it yields a proper renormalization group (RG) flow.
Strongly Correlated Electrons Statistical Mechanics High Energy Physics - Theory Quantum Physics
