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Found 3 papers, 1 papers with code
WiseR: An end-to-end structure learning and deployment framework for causal graphical models
Structure learning offers an expressive, versatile and explainable approach to causal and mechanistic modeling of complex biological data.
Harnessing GANs for Zero-shot Learning of New Classes in Visual Speech Recognition
To solve this problem, we present a novel approach to zero-shot learning by generating new classes using Generative Adversarial Networks (GANs), and show how the addition of unseen class samples increases the accuracy of a VSR system by a significant margin of 27% and allows it to handle speaker-independent out-of-vocabulary phrases.
Learning to Address Health Inequality in the United States with a Bayesian Decision Network
In this work, we reveal actionable interventions for decreasing the longevity-gap in the United States by analyzing a County-level data resource containing healthcare, socio-economic, behavioral, education and demographic features.
