Prediction-Constrained Training for Semi-Supervised Mixture and Topic Models. - Michael C. Hughes; Leah Weiner; Gabriel Hope; Thomas H. McCoy Jr.; Roy H. Perlis; Erik B. Sudderth; Finale Doshi-Velez (CoRR, 2017)

Prediction-Constrained Topic Models for Antidepressant Recommendation. - Michael C. Hughes; Gabriel Hope; Leah Weiner; Thomas H. McCoy Jr.; Roy H. Perlis; Erik B. Sudderth; Finale Doshi-Velez (CoRR, 2017)

Semi-Supervised Prediction-Constrained Topic Models. - Michael C. Hughes; Gabriel Hope; Leah Weiner; Thomas H. McCoy Jr.; Roy H. Perlis; Erik B. Sudderth; Finale Doshi-Velez (AISTATS, 2018)

Learning Consistent Deep Generative Models from Sparse Data via Prediction Constraints. - Gabriel Hope; Madina Abdrakhmanova; Xiaoyin Chen; Michael C. Hughes; Erik B. Sudderth (CoRR, 2020)

A decoder suffices for query-adaptive variational inference. - Sakshi Agarwal; Gabriel Hope; Ali Younis; Erik B. Sudderth (UAI, 2023)

Unbiased Learning of Deep Generative Models with Structured Discrete Representations. - Harry Bendekgey; Gabriel Hope; Erik B. Sudderth (CoRR, 2023)

Prediction-Constrained Latent Variable Models - Gabriel Hope (2023)