24 citations · 44 across the 7 of their papers we have counts for
7 papers
Neural Causal Abstractions
Kevin Xia, Elias Bareinboim
The abilities of humans to understand the world in terms of cause and effect relationships, as well as to compress information into abstract concepts, are two hallmark features of…
Counterfactual Image Editing
Yushu Pan, Elias Bareinboim
Counterfactual image editing is an important task in generative AI, which asks how an image would look if certain features were different. The current literature on the topic focus…
A Causal Framework for Decomposing Spurious Variations
Drago Plecko, Elias Bareinboim
One of the fundamental challenges found throughout the data sciences is to explain why things happen in specific ways, or through which mechanisms a certain variable exerts inf…
Causal Fairness for Outcome Control
Drago Plecko, Elias Bareinboim
As society transitions towards an AI-based decision-making infrastructure, an ever-increasing number of decisions once under control of humans are now delegated to automated system…
Sequential Causal Imitation Learning with Unobserved Confounders
Daniel Kumor, Junzhe Zhang, Elias Bareinboim
"Monkey see monkey do" is an age-old adage, referring to naïve imitation without a deep understanding of a system's underlying mechanics. Indeed, if a demonstrator has access to in…
Causal Imitation Learning with Unobserved Confounders
Junzhe Zhang, Daniel Kumor, Elias Bareinboim
One of the common ways children learn is by mimicking adults. Imitation learning focuses on learning policies with suitable performance from demonstrations generated by an expert,…