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Found 8 papers, 1 papers with code
Character-level Japanese Text Generation with Attention Mechanism for Chest Radiography Diagnosis
And, we were confirmed from the generated findings that the proposed method was able to consider the orthographic variants.
Improving Bi-directional Generation between Different Modalities with Variational Autoencoders
However, we found that when this model attempts to generate a large dimensional modality missing at the input, the joint representation collapses and this modality cannot be generated successfully.
Toward learning better metrics for sequence generation training with policy gradient
The partial reward function is a reward function for a partial sequence of a certain length.
Censoring Representations with Multiple-Adversaries over Random Subspaces
AFL learn such a representations by training the networks to deceive the adversary that predict the sensitive information from the network, and therefore, the success of the AFL heavily relies on the choice of the adversary.
Okutama-Action: An Aerial View Video Dataset for Concurrent Human Action Detection
Despite significant progress in the development of human action detection datasets and algorithms, no current dataset is representative of real-world aerial view scenarios.
Neural Machine Translation with Latent Semantic of Image and Text
The report of earlier studies has introduced a latent variable to capture the entire meaning of sentence and achieved improvement on attention-based Neural Machine Translation.
Joint Multimodal Learning with Deep Generative Models
As described herein, we propose a joint multimodal variational autoencoder (JMVAE), in which all modalities are independently conditioned on joint representation.
Generative Adversarial Nets from a Density Ratio Estimation Perspective
Generative adversarial networks (GANs) are successful deep generative models.
