Poster "observational data" Papers

13 papers found

Bi-Level Decision-Focused Causal Learning for Large-Scale Marketing Optimization: Bridging Observational and Experimental Data

Shuli Zhang, Hao Zhou, Jiaqi Zheng et al.

NEURIPS 2025arXiv:2510.19517

Causal Discovery via Bayesian Optimization

Bao Duong, Sunil Gupta, Thin Nguyen

ICLR 2025arXiv:2501.14997
1
citations

Causal LLM Routing: End-to-End Regret Minimization from Observational Data

Asterios Tsiourvas, Wei Sun, Georgia Perakis

NEURIPS 2025arXiv:2505.16037
7
citations

Differentially private learners for heterogeneous treatment effects

Maresa Schröder, Valentyn Melnychuk, Stefan Feuerriegel

ICLR 2025arXiv:2503.03486
3
citations

Efficient Causal Decision Making with One-sided Feedback

Jianing Chu, Shu Yang, Wenbin Lu et al.

ICLR 2025
1
citations

Multi-Accurate CATE is Robust to Unknown Covariate Shifts

Angela Zhou, Christoph Kern, Michael Kim

ICLR 2025
3
citations

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 2024

Causal Inference out of Control: Estimating Performativity without Treatment Randomization

Gary Cheng, Moritz Hardt, Celestine Mendler-Dünner

ICML 2024

Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias

Baohong Li, Haoxuan Li, Ruoxuan Xiong et al.

ICML 2024

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

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

ICML 2024arXiv:2406.02464
10
citations

PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect

Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh et al.

ICML 2024arXiv:2406.03864
3
citations

Stable Differentiable Causal Discovery

Achille Nazaret, Justin Hong, Elham Azizi et al.

ICML 2024arXiv:2311.10263
24
citations

Statistical Inference Under Constrained Selection Bias

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

ICML 2024arXiv:2306.03302