Causal Effect

Causal effect estimation aims to determine the impact of an intervention or treatment on an outcome, accounting for confounding factors that might obscure the true relationship. Current research focuses on improving estimation accuracy and robustness, particularly in complex settings with high-dimensional data, multiple treatments, and unobserved variables, employing techniques like double machine learning, graph neural networks, and Bayesian methods. These advancements are crucial for reliable causal inference across diverse fields, enabling more informed decision-making in areas such as healthcare, social sciences, and business, where understanding cause-and-effect relationships is paramount.

Papers

March 1, 2022

On Testability of the Front-Door Model via Verma Constraints
Rohit Bhattacharya, Razieh Nabi
Causal Effect Participation Constraint Unobserved Confounders Instrumental Variable Unmeasured Confounding Front Door Criterion Requirement Testability

February 28, 2022

Estimating causal effects with optimization-based methods: A review and empirical comparison
Martin Cousineau, Vedat Verter, Susan A. Murphy, Joelle Pineau
Narrative Review Causal Inference Causal Effect Optimization Method Empirical Comparison

February 25, 2022

Off-Policy Evaluation with Policy-Dependent Optimization Response
Wenshuo Guo, Michael I. Jordan, Angela Zhou
Causal Inference Causal Effect Policy Evaluation Policy Optimization

February 22, 2022

February 7, 2022

January 22, 2022

Causal effect of racial bias in data and machine learning algorithms on user persuasiveness & discriminatory decision making: An Empirical Study
Kinshuk Sengupta, Praveen Ranjan Srivastava
Empirical Study Absolute Stance Bias Causal Effect Biased Datasets Racial Bias Societal Bias Persuasive Argument Discriminatory Decision Biased Model

January 20, 2022

Generalizing Off-Policy Evaluation From a Causal Perspective For Sequential Decision-Making
Sonali Parbhoo, Shalmali Joshi, Finale Doshi-Velez
Causal Effect Policy Evaluation Sequential Decision

January 10, 2022

Style, Content, and the Success of Ideas
Reihane Boghrati, Jonah Berger, Grant Packard
Natural Language Processing Causal Effect Style Consistency Financial Success Human Generated Idea Temporal Perspective

December 19, 2021

Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies
Lu Cheng, Ruocheng Guo, Huan Liu
Causal Inference Causal Effect Causal Effect Estimation Empirical Evaluation Proxy Dataset Customer Review Restaurant Review

November 24, 2021

Matching Learned Causal Effects of Neural Networks with Domain Priors
Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N Balasubramanian, Amit Sharma
Neural Network Causal Effect Causal Relationship Structural Causal Model Matching Accuracy Domain Prior True Causal

November 19, 2021

A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling
Eustache Diemert, Artem Betlei, Christophe Renaudin, Massih-Reza Amini, Théophane Gregoir, Thibaud Rahier
Causal Effect Large Scale Benchmark Uplift Modeling Individual Treatment Effect Treatment Assignment Causal Inference Task Treatment Effect Estimation

November 16, 2021

Causal policy ranking
Daniel McNamee, Hana Chockler
Reinforcement Learning Causal Effect Counterfactual Reasoning Causal Learning Algorithm

November 12, 2021

ADCB: An Alzheimer's disease benchmark for evaluating observational estimators of causal effects
Newton Mwai Kinyanjui, Fredrik D. Johansson
Alzheimer'S Disease Causal Effect Causal Effect Estimation Observational Data Causal Inference Task Heterogeneous Effect Diagnostic Reasoning Benchmark

November 11, 2021

Variational Auto-Encoder Architectures that Excel at Causal Inference
Negar Hassanpour, Russell Greiner
Causal Inference Causal Effect Generative Approach Variational Auto Observational Data

November 8, 2021

Clustering and Structural Robustness in Causal Diagrams
Santtu Tikka, Jouni Helske, Juha Karvanen
Causal Effect Causal Relation Well Clustered Graph Transit Network

November 3, 2021

Leveraging Causal Graphs for Blocking in Randomized Experiments
Abhishek Kumar Umrawal
Causal Graph Causal Effect Multi Modal Outer Arithmetic Block Randomized Experiment Causal Markov

May 19, 2021

Multiply Robust Causal Mediation Analysis with Continuous Treatments
Yizhen Xu, Numair Sani, AmirEmad Ghassami, Ilya Shpitser
Causal Effect Value Function Influence Function Causal Mediation Analysis Valued Treatment

Causal Effect

Papers

On Testability of the Front-Door Model via Verma Constraints

Estimating causal effects with optimization-based methods: A review and empirical comparison

Off-Policy Evaluation with Policy-Dependent Optimization Response

Policy Evaluation for Temporal and/or Spatial Dependent Experiments

Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for Introduced Unfairness

Stochastic Causal Programming for Bounding Treatment Effects

Targeted-BEHRT: Deep learning for observational causal inference on longitudinal electronic health records

Personalized Public Policy Analysis in Social Sciences using Causal-Graphical Normalizing Flows

Causal effect of racial bias in data and machine learning algorithms on user persuasiveness & discriminatory decision making: An Empirical Study

Generalizing Off-Policy Evaluation From a Causal Perspective For Sequential Decision-Making

Style, Content, and the Success of Ideas

Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies

Matching Learned Causal Effects of Neural Networks with Domain Priors

A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling

Causal policy ranking

ADCB: An Alzheimer's disease benchmark for evaluating observational estimators of causal effects

Variational Auto-Encoder Architectures that Excel at Causal Inference

Clustering and Structural Robustness in Causal Diagrams

Leveraging Causal Graphs for Blocking in Randomized Experiments

Multiply Robust Causal Mediation Analysis with Continuous Treatments