Beijing Baidu Netcom Science Technology Co., Ltd

Beijing Baidu Netcom Science and Technology Co., Ltd.

Weihua Peng

Jian Qiao Sun

Yuguang Chen

Weijian Xu

Yehan Zheng

Guangzhi Sheng

Shangru Zhong

Chenye Wu

Donghai Bian

Yuwei Wu

A method of training an image generation model, and a method of generating an image. A specific implementation solution includes: acquiring a first image sample and a first text sample matched with the first image sample; performing an enhancement on at least one type of sample in the first image sample and the first text sample according to a predetermined knowledge graph, so as to obtain at least one type of sample in a second image sample obtained by the enhancement and a second text sample obtained by the enhancement; and training the image generation model according to a training set selected from a first training set, a second training set or a third training set, until the image generation model converges.

Method of training image generation model, and method of generating image

An information processing method, an electronic device, and a storage medium are provided, which relate to the field of artificial intelligence technologies such as big data, knowledge graphs, deep learning and the like. The method includes: determining a first independence relationship according to a plurality of variables and values respectively corresponding to the plurality of variables, wherein the first independence relationship includes: at least two variables of the plurality of variables being relatively independent; determining a first adjustment scheme according to the plurality of variables and the first independence relationship; adjusting the first independence relationship according to the first adjustment scheme, to obtain a second independence relationship; and obtaining a causal relationship information processing result according to the second independence relationship.

Information processing method, electronic device, and storage medium

A method for generating a relationship of events includes: obtaining a statement of a first event and a statement of a second event; generating a word sequence vector with first granularity and a word sequence vector with second granularity based on the statement of the first event; generating a word sequence vector with third granularity and a word sequence vector with fourth granularity based on the statement of the second event; generating a first fusion vector based on the word sequence vector with first granularity and the word sequence vector with second granularity; generating a second fusion vector based on the word sequence vector with third granularity and the word sequence vector with fourth granularity; and determining a relationship between the first event and the second event based on the first fusion vector and the second fusion vector.

Method, electronic device, and storage medium for generating relationship of events

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Beijing, China

Weihua Peng