:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Barroso, Filipe, Gomes, Diogo, Baxter, Gareth J.
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Methodology
Online Access:	https://arxiv.org/abs/2404.14460
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

HNCI: High-Dimensional Network Causal Inference
by: Du, Wenqin, et al.
Published: (2024)

Bayesian Causal Inference with Gaussian Process Networks
by: Giudice, Enrico, et al.
Published: (2024)

An Overview of Causal Inference using Kernel Embeddings
by: Sejdinovic, Dino
Published: (2024)

Topological Causal Effects
by: Kim, Kwangho, et al.
Published: (2026)

Structure Maintained Representation Learning Neural Network for Causal Inference
by: Sun, Yang, et al.
Published: (2025)

Integrating Causal Inference with Graph Neural Networks for Alzheimer's Disease Analysis
by: Peddi, Pranay Kumar, et al.
Published: (2025)

Testing Generalizability in Causal Inference
by: Manela, Daniel de Vassimon, et al.
Published: (2024)

Causal Inference with the "Napkin Graph"
by: Guo, Anna, et al.
Published: (2025)

A Semiparametric Approach to Causal Inference
by: Zhang, Archer Gong, et al.
Published: (2024)

Valid Inference After Causal Discovery
by: Gradu, Paula, et al.
Published: (2022)

Probabilistic Modelling is Sufficient for Causal Inference
by: Mlodozeniec, Bruno, et al.
Published: (2025)

Controllable Generative Sandbox for Causal Inference
by: Zhang, Qi, et al.
Published: (2026)

Causal Inference on Networks under Misspecified Exposure Mappings: A Partial Identification Framework
by: Schröder, Maresa, et al.
Published: (2026)

Regularizing Extrapolation in Causal Inference
by: Arbour, David, et al.
Published: (2025)

Causal Inference with Complex Treatments: A Survey
by: Wang, Yingrong, et al.
Published: (2024)

Bayesian Sensitivity of Causal Inference Estimators under Evidence-Based Priors
by: Dhawan, Nikita, et al.
Published: (2026)

Causal Rule Ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment Effects
by: Bargagli-Stoffi, Falco J., et al.
Published: (2020)

Marginal Causal Flows for Validation and Inference
by: Manela, Daniel de Vassimon, et al.
Published: (2024)

Diffusion-aware Censored Gaussian Processes for Demand Modelling
by: Rodrigues, Filipe
Published: (2025)

Over-Squashing in GNNs and Causal Inference of Rewiring Strategies
by: Saber, Danial, et al.
Published: (2025)

A Latent Causal Inference Framework for Ordinal Variables
by: Scauda, Martina, et al.
Published: (2025)

Causal Inference on Stopped Random Walks in Online Advertising
by: Yu, Jia Yuan
Published: (2026)

Causal Inference for Preprocessed Outcomes with an Application to Functional Connectivity
by: Wang, Zihang, et al.
Published: (2026)

The Local Approach to Causal Inference under Network Interference
by: Auerbach, Eric, et al.
Published: (2021)

New User Event Prediction Through the Lens of Causal Inference
by: Yuchi, Henry Shaowu, et al.
Published: (2024)

Causal Inference with Latent Variables: Recent Advances and Future Prospectives
by: Zhu, Yaochen, et al.
Published: (2024)

Causal Inference with Categorical Unobserved Confounder via Mixture Learning
by: Saha, Aytijhya, et al.
Published: (2026)

A Sensitivity Approach to Causal Inference Under Limited Overlap
by: Ma, Yuanzhe, et al.
Published: (2025)

Minimum Specification Perturbation: Robustness as Distance-to-Falsification in Causal Inference
by: Dang, Hoang, et al.
Published: (2026)

Causality-Encoded Diffusion Models for Interventional Sampling and Edge Inference
by: Chen, Li, et al.
Published: (2026)

Applied Causal Inference Powered by ML and AI
by: Chernozhukov, Victor, et al.
Published: (2024)

Towards Representation Learning for Weighting Problems in Design-Based Causal Inference
by: Clivio, Oscar, et al.
Published: (2024)

Semiparametric Double Reinforcement Learning with Applications to Long-Term Causal Inference
by: van der Laan, Lars, et al.
Published: (2025)

An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
by: Liang, Biyonka, et al.
Published: (2023)

Causal Inference Isn't Special: Why It's Just Another Prediction Problem
by: Fernández-Loría, Carlos
Published: (2025)

Forests for Differences: Robust Causal Inference Beyond Parametric DiD
by: Souto, Hugo Gobato, et al.
Published: (2025)

Improving Generative Methods for Causal Evaluation via Simulation-Based Inference
by: Amaranath, Pracheta, et al.
Published: (2025)

Flexible Nonparametric Inference for Causal Effects under the Front-Door Model
by: Guo, Anna, et al.
Published: (2023)

Proximal Causal Inference With Text Data
by: Chen, Jacob M., et al.
Published: (2024)

Doubly Robust Inference in Causal Latent Factor Models
by: Abadie, Alberto, et al.
Published: (2024)