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Found 4 papers, 1 papers with code
Overcoming Mode Collapse with Adaptive Multi Adversarial Training
Generative Adversarial Networks (GANs) are a class of generative models used for various applications, but they have been known to suffer from the mode collapse problem, in which some modes of the target distribution are ignored by the generator.
Mitigating Mode Collapse by Sidestepping Catastrophic Forgetting
Generative Adversarial Networks (GANs) are a class of generative models used for various applications, but they have been known to suffer from the mode collapse problem, in which some modes of the target distribution are ignored by the generator.
Goal-driven Command Recommendations for Analysts
With this assumption, we would like to assist the analytics process of a user through command recommendations.
IITK-RSA at SemEval-2020 Task 5: Detecting Counterfactuals
This paper describes our efforts in tackling Task 5 of SemEval-2020.
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