Gabriel Hope

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 6

Top Topics

Variational Inference

Boltzmann Machine

Top Venues

Publications

Sakshi Agarwal, Gabriel Hope, Ali Younis, Erik B. Sudderth
A decoder suffices for query-adaptive variational inference. UAI (2023)
Harry Bendekgey, Gabriel Hope, Erik B. Sudderth
Unbiased Learning of Deep Generative Models with Structured Discrete Representations. CoRR (2023)
Gabriel Hope, Madina Abdrakhmanova, Xiaoyin Chen, Michael C. Hughes, Erik B. Sudderth
Learning Consistent Deep Generative Models from Sparse Data via Prediction Constraints. CoRR (2020)
Michael C. Hughes, Gabriel Hope, Leah Weiner, Thomas H. McCoy Jr., Roy H. Perlis, Erik B. Sudderth, Finale Doshi-Velez
Semi-Supervised Prediction-Constrained Topic Models. AISTATS (2018)
Michael C. Hughes, Leah Weiner, Gabriel Hope, Thomas H. McCoy Jr., Roy H. Perlis, Erik B. Sudderth, Finale Doshi-Velez
Prediction-Constrained Training for Semi-Supervised Mixture and Topic Models. CoRR (2017)
Michael C. Hughes, Gabriel Hope, Leah Weiner, Thomas H. McCoy Jr., Roy H. Perlis, Erik B. Sudderth, Finale Doshi-Velez
Prediction-Constrained Topic Models for Antidepressant Recommendation. CoRR (2017)