Dec 17, 2022 · We propose a novel zero-shot knowledge graph framework based on stochastic and dual adversarial GAN (SDA) which successfully improves the ...

Another contribution of our approach is the integration of domain/expert knowledge at different stages of the learning process of a Bayesian network: while ...

In this work, we propose a novel zero-shot KG framework based on stochastic and dual adversarial GAN (SDA) to better mine the association between semantic ...

Stochastic and Dual Adversarial GAN-Boosted Zero-Shot Knowledge Graph ... Zero-shot knowledge graph (KG) has gained much research attention in recent years. Due ...

Oct 22, 2024 · For this purpose, we leverage Generative Adversarial Networks (GANs) to establish the connection between text and knowledge graph domain: The ...

Apr 9, 2024 · In this paper, we propose a novel end- to-end framework, consisting of three components, i.e., multimodal learner, structure consolidator, and ...

Zero-shot learning relies on semantic class representations such as hand-engineered attributes or learned embeddings to predict classes without any labeled ...

Aug 25, 2022 · Zero-shot learning relies on semantic class representations such as hand-engineered attributes or learned embeddings to predict classes ...

This paper studies the problem of generalized zero-shot learning which requires the model to train on image-label pairs from some seen classes and test on ...

Abstract: Zero-Shot Action Recognition (ZSAR) aims to recognise action classes in videos that have never been seen during model training.