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Found 5 papers, 3 papers with code
Prb-GAN: A Probabilistic Framework for GAN Modelling
Generative adversarial networks (GANs) are very popular to generate realistic images, but they often suffer from the training instability issues and the phenomenon of mode loss.
Deep Bayesian Network for Visual Question Generation
This is a Bayesian framework and the results show a remarkable similarity to natural questions as validated by a human study.
Revisiting Paraphrase Question Generator using Pairwise Discriminator
One way to ensure this is by adding constraints for true paraphrase embeddings to be close and unrelated paraphrase candidate sentence embeddings to be far.
Multimodal Differential Network for Visual Question Generation
Generating natural questions from an image is a semantic task that requires using visual and language modality to learn multimodal representations.
Learning Semantic Sentence Embeddings using Sequential Pair-wise Discriminator
One way to ensure this is by adding constraints for true paraphrase embeddings to be close and unrelated paraphrase candidate sentence embeddings to be far.
