Poster "causal inference" Papers
40 papers found
A Counterfactual Semantics for Hybrid Dynamical Systems
Andy Zane, Dmitry Batenkov, Rafal Urbaniak et al.
Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference
Anpeng Wu, Haiyi Qiu, Zhengming Chen et al.
Causal Order: The Key to Leveraging Imperfect Experts in Causal Inference
Aniket Vashishtha, Abbavaram Gowtham Reddy, Abhinav Kumar et al.
Data Fusion for Partial Identification of Causal Effects
Quinn Lanners, Cynthia Rudin, Alexander Volfovsky et al.
Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm
Mathieu Chevalley, Patrick Schwab, Arash Mehrjou
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.
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.
Causal Discovery with Fewer Conditional Independence Tests
Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler
Causal Inference from Competing Treatments
Ana-Andreea Stoica, Vivian Y. Nastl, Moritz Hardt
Causal Inference out of Control: Estimating Performativity without Treatment Randomization
Gary Cheng, Moritz Hardt, Celestine Mendler-Dünner
Causal-IQA: Towards the Generalization of Image Quality Assessment Based on Causal Inference
Yan Zhong, Xingyu Wu, Li Zhang et al.
Causality Based Front-door Defense Against Backdoor Attack on Language Models
Yiran Liu, Xiaoang Xu, Zhiyi Hou et al.
COIN-Matting: Confounder Intervention for Image Matting
Zhaohe Liao, Jiangtong Li, Jun Lan et al.
Collaborative Heterogeneous Causal Inference Beyond Meta-analysis
Tianyu Guo, Sai Praneeth Karimireddy, Michael Jordan
Continuous Treatment Effects with Surrogate Outcomes
Zhenghao Zeng, David Arbour, Avi Feller et al.
DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation
Qinshuo Liu, Zixin Wang, Xi'an Li et al.
From Geometry to Causality- Ricci Curvature and the Reliability of Causal Inference on Networks
Amirhossein Farzam, Allen Tannenbaum, Guillermo Sapiro
Graph Neural Network Causal Explanation via Neural Causal Models
Arman Behnam, Binghui Wang
Incorporating Information into Shapley Values: Reweighting via a Maximum Entropy Approach
Darya Biparva, Donatello Materassi
Inferring the Long-Term Causal Effects of Long-Term Treatments from Short-Term Experiments
Allen Tran, Aurelien Bibaut, Nathan Kallus
Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects
Aaron Fisher
Language Models Represent Beliefs of Self and Others
Wentao Zhu, Zhining Zhang, Yizhou Wang
Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias
Baohong Li, Haoxuan Li, Ruoxuan Xiong et al.
Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference
Md Musfiqur Rahman, Murat Kocaoglu
On Positivity Condition for Causal Inference
Inwoo Hwang, Yesong Choe, Yeahoon Kwon et al.
Position: AI/ML Influencers Have a Place in the Academic Process
Iain Xie Weissburg, Mehir Arora, Xinyi Wang et al.
Position: Is machine learning good or bad for the natural sciences?
David W. Hogg, Soledad Villar
Predictive Coding beyond Correlations
Tommaso Salvatori, Luca Pinchetti, Amine M'Charrak et al.
Predictive Performance Comparison of Decision Policies Under Confounding
Luke Guerdan, Amanda Coston, Ken Holstein et al.
Reducing Balancing Error for Causal Inference via Optimal Transport
Yuguang Yan, Hao Zhou, Zeqin Yang et al.
Towards Causal Foundation Model: on Duality between Optimal Balancing and Attention
Jiaqi Zhang, Joel Jennings, Agrin Hilmkil et al.
Two-Stage Shadow Inclusion Estimation: An IV Approach for Causal Inference under Latent Confounding and Collider Bias
Baohong Li, Anpeng Wu, Ruoxuan Xiong et al.