Abstract: The present invention discloses a cup lid and a thermos cup; the cup lid includes a cup lid body, the cup lid body includes a connection portion connected to a cup body, the cup lid body is provided with an opening, the opening is connected with a connector by a detachable structure, the connector is provided with a first mouth, and an outer wall of the first mouth and the opening form a second mouth. The first mouth serves as a sipping port and the second mouth serves as a direct drinking port, so that the present invention has a double drinking function, and the first mouth is detachably connected for easy cleaning.

Abstract: A method for training a probabilistic encoder-decoder having a latent space, the method including: extracting different types of medical data for a group of individuals; creating a data matrix X including the extracted medical data, wherein each row of the data matrix X includes data for one of the group of individuals; creating condition matrix C including features to define a clinical condition, wherein each row of the condition matrix C includes the condition data for one of the group of individuals; and training the encoder and the decoder to learn the latent space by minimizing the reconstruction loss and using a regularization effect to force clinically similar inputs to be close together in the latent space.

Abstract: A method for training a probabilistic encoder-decoder having a latent space, the method including: extracting different types of medical data for a group of individuals; creating a data matrix X including the extracted medical data, wherein each row of the data matrix X includes data for one of the group of individuals; creating condition matrix C including features to define a clinical condition, wherein each row of the condition matrix C includes the condition data for one of the group of individuals; and training the encoder and the decoder to learn the latent space by minimizing the reconstruction loss and using a regularization effect to force clinically similar inputs to be close together in the latent space.