5 citations · 15 across the 6 of their papers we have counts for
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cs.LG2020
Learning Consistent Deep Generative Models from Sparse Data via Prediction Constraints
Gabriel Hope, Madina Abdrakhmanova, Xiaoyin Chen +2
We develop a new framework for learning variational autoencoders and other deep generative models that balances generative and discriminative goals. Our framework optimizes model p…
cs.LG2017★ 5 cited
Prediction-Constrained Topic Models for Antidepressant Recommendation
Michael C. Hughes, Gabriel Hope, Leah Weiner +4
Supervisory signals can help topic models discover low-dimensional data representations that are more interpretable for clinical tasks. We propose a framework for training supervis…