For a quarter century, cosmology has rested on a simple but audacious idea: that a fixed “cosmological constant” drives the ...
Abstract: Existing ac/dc power flow computations necessitate sequential convergence-oriented trial-and-error under various dc control modes, rising computational ...
Abstract: In this study, we propose a Bayesian seismic tomography inference method using physics-informed neural networks (PINNs). PINN represents a recent advance in deep learning, offering the ...