Abstract: Embodiments of the present application provide electric power supply methods and electric power supply systems related to the field of electrical energy technology. An electric power supply method includes: acquiring an electrical energy parameter of electrical energy delivered by an upstream power supply system, and determining, based on the electrical energy parameter, whether a preset power supply condition for supplying power to a downstream target power-consuming system is met; determining a target distribution port corresponding to the target power-consuming system from a plurality of preset distribution ports when the preset power supply condition is met; controlling a supply of electric power to the target power-consuming system through the target distribution port.

Abstract: A machine learning architecture employs two machine learning networks that are joined by a statistical model allowing the imposition of a predetermined statistical model family into a learning process in which the networks translate between and data types. For example, the statistical model may enforce a Gaussian conditional probability between the latent variables in the translation process. In one application, MRI images may be translated into PET images with reduced mode collapse, blurring, or other “averaging” type behaviors.

Abstract: Embodiments of the present application provide electric power supply methods and electric power supply systems related to the field of electrical energy technology. An electric power supply method includes: acquiring an electrical energy parameter of electrical energy delivered by an upstream power supply system, and determining, based on the electrical energy parameter, whether a preset power supply condition for supplying power to a downstream target power-consuming system is met; determining a target distribution port corresponding to the target power-consuming system from a plurality of preset distribution ports when the preset power supply condition is met; controlling a supply of electric power to the target power-consuming system through the target distribution port.

Abstract: A machine learning architecture employs two machine learning networks that are joined by a statistical model allowing the imposition of a predetermined statistical model family into a learning process in which the networks translate between and data types. For example, the statistical model may enforce a Gaussian conditional probability between the latent variables in the translation process. In one application, MRI images may be translated into PET images with reduced mode collapse, blurring, or other “averaging” type behaviors.