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Abstract: Composite power system reliability evaluation using Monte Carlo simulation often suffers from high computational cost due to the difficulty in capturing rare loss-of-load states. To address ...

We present Bayesian Diffusion Models (BDM), a prediction algorithm that performs effective Bayesian inference by tightly coupling the top-down (prior) information with the bottom-up (data-driven) ...

Abstract: Deep Forest, a powerful alternative to deep neural networks, has gained much attention due to its advantages, such as low complexity, minimal hyperparameter requirements, and strong ...