1 citations · 1 across the 2 of their papers we have counts for
5 papers
Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration
Longlin Yu, Tianyu Xie, Yu Zhu +3
Semi-implicit variational inference (SIVI) has been introduced to expand the analytical variational families by defining expressive semi-implicit distributions in a hierarchical ma…
Semi-Implicit Variational Inference via Score Matching
Longlin Yu, Cheng Zhang
Semi-implicit variational inference (SIVI) greatly enriches the expressiveness of variational families by considering implicit variational distributions defined in a hierarchical m…
Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning
Matthew Ashman, Chao Ma, Agrin Hilmkil +2
Latent confounding has been a long-standing obstacle for causal reasoning from observational data. One popular approach is to model the data using acyclic directed mixed graphs (AD…
Optimal transport for causal discovery
Ruibo Tu, Kun Zhang, Hedvig Kjellström +1
To determine causal relationships between two variables, approaches based on Functional Causal Models (FCMs) have been proposed by properly restricting model classes; however, the…
Diagnostic Prediction Using Discomfort Drawings
Cheng Zhang, Hedvig Kjellstrom, Bo C. Bertilson
In this paper, we explore the possibility to apply machine learning to make diagnostic predictions using discomfort drawings. A discomfort drawing is an intuitive way for patients…