6 citations · 6 across the 7 of their papers we have counts for
3 papers · 1 filter
Beyond Additivity: Causal Discovery in Location-Scale Noise Models with Hidden Variables
Mariyam Khan, Shohei Shimizu, Thong Pham
We study causal discovery from observational data when some variables are hidden and the data-generating process follows a location-scale noise model (LSNM). Existing methods that…
Causal-discovery-based root-cause analysis and its application in time-series prediction error diagnosis
Hiroshi Yokoyama, Ryusei Shingaki, Kaneharu Nishino +2
Recent rapid advancements of machine learning have greatly enhanced the accuracy of prediction models, but most models remain "black boxes", making prediction error diagnosis chall…
Scalable Counterfactual Distribution Estimation in Multivariate Causal Models
Thong Pham, Shohei Shimizu, Hideitsu Hino +1
We consider the problem of estimating the counterfactual joint distribution of multiple quantities of interests (e.g., outcomes) in a multivariate causal model extended from the cl…