2024 "observational data" Papers

14 papers found

A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective

Baohong Li, Haoxuan Li, Anpeng Wu et al.

ICML 2024poster

Automating the Selection of Proxy Variables of Unmeasured Confounders

Feng Xie, Zhengming Chen, Shanshan Luo et al.

ICML 2024spotlight

Causal Inference out of Control: Estimating Performativity without Treatment Randomization

Gary Cheng, Moritz Hardt, Celestine Mendler-Dünner

ICML 2024poster

Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing

Lokesh Nagalapatti, Akshay Iyer, Abir De et al.

AAAI 2024paperarXiv:2401.15447
12
citations

Fair Off-Policy Learning from Observational Data

Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel

ICML 2024oral

Federated Causality Learning with Explainable Adaptive Optimization

Dezhi Yang, Xintong He, Jun Wang et al.

AAAI 2024paperarXiv:2312.05540
13
citations

Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias

Baohong Li, Haoxuan Li, Ruoxuan Xiong et al.

ICML 2024poster

Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments

Jonas Schweisthal, Dennis Frauen, M van der Schaar et al.

ICML 2024poster

NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation

Abbvavaram Gowtham Reddy, Vineeth N Balasubramanian

AAAI 2024paperarXiv:2211.04370
1
citations

PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect

Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh et al.

ICML 2024poster

Probabilities of Causation with Nonbinary Treatment and Effect

Ang Li, Judea Pearl

AAAI 2024paperarXiv:2208.09568

s-ID: Causal Effect Identification in a Sub-population

Amir Mohammad Abouei, Ehsan Mokhtarian, Negar Kiyavash

AAAI 2024paperarXiv:2309.02281
4
citations

Stable Differentiable Causal Discovery

Achille Nazaret, Justin Hong, Elham Azizi et al.

ICML 2024poster

Statistical Inference Under Constrained Selection Bias

Santiago Cortes-Gomez, Mateo Dulce Rubio, Carlos Miguel Patiño et al.

ICML 2024poster