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Found 4 papers, 1 papers with code
Cross-modal Image Retrieval with Deep Mutual Information Maximization
Prior work usually uses a three-stage strategy to tackle this task: 1) extract the features of the inputs; 2) fuse the feature of the source image and its modified text to obtain fusion feature; 3) learn a similarity metric between the desired image and the source image + modified text by using deep metric learning.
Adaptive-Step Graph Meta-Learner for Few-Shot Graph Classification
The shared sub-structures between training classes and test classes are essential in few-shot graph classification.
Matching Text with Deep Mutual Information Estimation
Our approach, Text matching with Deep Info Max (TIM), is integrated with a procedure of unsupervised learning of representations by maximizing the mutual information between text matching neural network's input and output.
Hierarchical Graph Pooling with Structure Learning
HGP-SL incorporates graph pooling and structure learning into a unified module to generate hierarchical representations of graphs.
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