research
∙
06/08/2023
A Causal Framework for Decomposing Spurious Variations
One of the fundamental challenges found throughout the data sciences is ...
share
research
∙
06/08/2023
Causal Fairness for Outcome Control
As society transitions towards an AI-based decision-making infrastructur...
research
∙
06/08/2023
Reconciling Predictive and Statistical Parity: A Causal Approach
Since the rise of fair machine learning as a critical field of inquiry, ...
research
∙
06/01/2023
Nonparametric Identifiability of Causal Representations from Unknown Interventions
We study causal representation learning, the task of inferring latent ca...
research
∙
10/11/2022
Finding and Listing Front-door Adjustment Sets
Identifying the effects of new interventions from data is a significant ...
research
∙
09/30/2022
Neural Causal Models for Counterfactual Identification and Estimation
Evaluating hypothetical statements about how the world would be had a di...
research
∙
08/12/2022
Sequential Causal Imitation Learning with Unobserved Confounders
"Monkey see monkey do" is an age-old adage, referring to naïve imitation...
research
∙
08/12/2022
Causal Imitation Learning with Unobserved Confounders
One of the common ways children learn is by mimicking adults. Imitation ...
research
∙
07/23/2022
Causal Fairness Analysis
Decision-making systems based on AI and machine learning have been used ...
research
∙
04/26/2022
Causal Transportability for Visual Recognition
Visual representations underlie object recognition tasks, but they often...
research
∙
02/22/2022
Effect Identification in Cluster Causal Diagrams
One pervasive task found throughout the empirical sciences is to determi...
research
∙
10/12/2021
Partial Counterfactual Identification from Observational and Experimental Data
This paper investigates the problem of bounding counterfactual queries f...
research
∙
07/07/2021
Nested Counterfactual Identification from Arbitrary Surrogate Experiments
The Ladder of Causation describes three qualitatively different types of...
research
∙
07/02/2021
The Causal Neural Connection: Expressiveness, Learnability, and Inference
One of the central elements of any causal inference is an object called ...
research
∙
10/29/2019
Efficient Identification in Linear Structural Causal Models with Instrumental Cutsets
One of the most common mistakes made when performing data analysis is at...
research
∙
12/15/2018
Causal Identification under Markov Equivalence
Assessing the magnitude of cause-and-effect relations is one of the cent...
research
∙
09/11/2017
Budgeted Experiment Design for Causal Structure Learning
We study the problem of causal structure learning when the experimenter ...
research
∙
11/10/2015
Incorporating Knowledge into Structural Equation Models using Auxiliary Variables
In this paper, we extend graph-based identification methods by allowing ...
research
∙
03/05/2015
External Validity: From Do-Calculus to Transportability Across Populations
The generalizability of empirical findings to new environments, settings...
research
∙
12/29/2013
A General Algorithm for Deciding Transportability of Experimental Results
Generalizing empirical findings to new environments, settings, or popula...
research
∙
10/16/2012
