2025 "causal inference" Papers
29 papers found
A Cautionary Tale on Integrating Studies with Disparate Outcome Measures for Causal Inference
Harsh Parikh, Trang Nguyen, Elizabeth Stuart et al.
A Counterfactual Semantics for Hybrid Dynamical Systems
Andy Zane, Dmitry Batenkov, Rafal Urbaniak et al.
A Hierarchy of Graphical Models for Counterfactual Inferences
Hongshuo Yang, Elias Bareinboim
Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference
Anpeng Wu, Haiyi Qiu, Zhengming Chen et al.
Causality-guided Prompt Learning for Vision-language Models via Visual Granulation
Mengyu Gao, Qiulei Dong
Causal LLM Routing: End-to-End Regret Minimization from Observational Data
Asterios Tsiourvas, Wei Sun, Georgia Perakis
Causal Order: The Key to Leveraging Imperfect Experts in Causal Inference
Aniket Vashishtha, Abbavaram Gowtham Reddy, Abhinav Kumar et al.
Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets
Yuxin Wang, Maresa Schröder, Dennis Frauen et al.
Data Fusion for Partial Identification of Causal Effects
Quinn Lanners, Cynthia Rudin, Alexander Volfovsky et al.
DeCaFlow: A deconfounding causal generative model
Alejandro Almodóvar, Adrián Javaloy, Juan Parras et al.
Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm
Mathieu Chevalley, Patrick Schwab, Arash Mehrjou
Diverse Influence Component Analysis: A Geometric Approach to Nonlinear Mixture Identifiability
Hoang Son Nguyen, Xiao Fu
Gaussian Mixture Counterfactual Generator
Jong-Hoon Ahn, Akshay Vashist
Handling Missing Responses under Cluster Dependence with Applications to Language Model Evaluation
Zhenghao Zeng, David Arbour, Avi Feller et al.
Incremental Causal Effect for Time to Treatment Initialization
Andrew Ying, Zhichen Zhao, Ronghui Xu
It’s Hard to Be Normal: The Impact of Noise on Structure-agnostic Estimation
Jikai Jin, Lester Mackey, Vasilis Syrgkanis
Mind Control through Causal Inference: Predicting Clean Images from Poisoned Data
Mengxuan Hu, Zihan Guan, Yi Zeng et al.
Neural Causal Graph for Interpretable and Intervenable Classification
Jiawei Wang, Shaofei Lu, Da Cao et al.
Optimal Nuisance Function Tuning for Estimating a Doubly Robust Functional under Proportional Asymptotics
Sean McGrath, Debarghya Mukherjee, Rajarshi Mukherjee et al.
Path-specific effects for pulse-oximetry guided decisions in critical care
Kevin Zhang, Yonghan Jung, Divyat Mahajan et al.
Practical do-Shapley Explanations with Estimand-Agnostic Causal Inference
Álvaro Parafita, Tomas Garriga, Axel Brando et al.
Prediction-Powered Causal Inferences
Riccardo Cadei, Ilker Demirel, Piersilvio De Bartolomeis et al.
ProDAG: Projected Variational Inference for Directed Acyclic Graphs
Ryan Thompson, Edwin Bonilla, Robert Kohn
PUATE: Efficient ATE Estimation from Treated (Positive) and Unlabeled Units
Masahiro Kato, Fumiaki Kozai, RYO INOKUCHI
Standardizing Structural Causal Models
Weronika Ormaniec, Scott Sussex, Lars Lorch et al.
Stochastic Gradients under Nuisances
Facheng Yu, Ronak Mehta, Alex Luedtke et al.
Treatment Effect Estimation for Optimal Decision-Making
Dennis Frauen, Valentyn Melnychuk, Jonas Schweisthal et al.
Turning Sand to Gold: Recycling Data to Bridge On-Policy and Off-Policy Learning via Causal Bound
Tal Fiskus, Uri Shaham
Unveiling Environmental Sensitivity of Individual Gains in Influence Maximization
Xinyan Su, Zhiheng Zhang, Jiyan Qiu et al.