"observational data" Papers
21 papers found
Conference
Bi-Level Decision-Focused Causal Learning for Large-Scale Marketing Optimization: Bridging Observational and Experimental Data
Shuli Zhang, Hao Zhou, Jiaqi Zheng et al.
Causal Discovery via Bayesian Optimization
Bao Duong, Sunil Gupta, Thin Nguyen
Causal LLM Routing: End-to-End Regret Minimization from Observational Data
Asterios Tsiourvas, Wei Sun, Georgia Perakis
Differentially private learners for heterogeneous treatment effects
Maresa Schröder, Valentyn Melnychuk, Stefan Feuerriegel
Efficient Causal Decision Making with One-sided Feedback
Jianing Chu, Shu Yang, Wenbin Lu et al.
Learning Structural Causal Models from Ordering: Identifiable Flow Models
Minh Khoa Le, Kien Do, Truyen Tran
Multi-Accurate CATE is Robust to Unknown Covariate Shifts
Angela Zhou, Christoph Kern, Michael Kim
A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective
Baohong Li, Haoxuan Li, Anpeng Wu et al.
Automating the Selection of Proxy Variables of Unmeasured Confounders
Feng Xie, Zhengming Chen, Shanshan Luo et al.
Causal Inference out of Control: Estimating Performativity without Treatment Randomization
Gary Cheng, Moritz Hardt, Celestine Mendler-Dünner
Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing
Lokesh Nagalapatti, Akshay Iyer, Abir De et al.
Fair Off-Policy Learning from Observational Data
Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel
Federated Causality Learning with Explainable Adaptive Optimization
Dezhi Yang, Xintong He, Jun Wang et al.
Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias
Baohong Li, Haoxuan Li, Ruoxuan Xiong et al.
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments
Jonas Schweisthal, Dennis Frauen, M van der Schaar et al.
NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation
Abbvavaram Gowtham Reddy, Vineeth N Balasubramanian
PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect
Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh et al.
Probabilities of Causation with Nonbinary Treatment and Effect
Ang Li, Judea Pearl
s-ID: Causal Effect Identification in a Sub-population
Amir Mohammad Abouei, Ehsan Mokhtarian, Negar Kiyavash
Stable Differentiable Causal Discovery
Achille Nazaret, Justin Hong, Elham Azizi et al.
Statistical Inference Under Constrained Selection Bias
Santiago Cortes-Gomez, Mateo Dulce Rubio, Carlos Miguel Patiño et al.