Abstract: Time series data can be represented in both the time and frequency domains, with the time domainemphasizing local dependencies and the frequency domain highlighting global dependencies. To ...
Compressing chess endgame tablebases and universal evaluation with Relational Graph Neural Networks (RGNN), attention mechanisms, and triple-head outputs. Neural Tablebases explores whether chess ...
Abstract: This work explores the use of Physics-Informed Neural Networks (PINNs) and a newly proposed approach, called the STacked Adaptive Residual PINN (STAR-PINN), to solve magnetic diffusion ...
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