arXiv Machine Learning June 3, 2026 By Masahiro Tanaka

Estimating Bidirectional Causal Effects with Large Scale Online Kernel Learning

Read the original on arXiv Machine Learning →

arXiv:2511. 05050v3 Announce Type: replace-cross Abstract: In this study, a scalable online kernel learning framework is proposed for estimating bidirectional causal effects in systems characterized by mutual dependence and heteroskedasticity.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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arXiv Machine Learning

Jun 17

Instrumental and Proximal Causal Inference with Gaussian Processes

arXiv:2603. 02159v2 Announce Type: replace-cross Abstract: Instrumental variable (IV) and proximal causal learning (Proxy) methods are central frameworks for causal inference in the presence of unobserved confounding.

By Yuqi Zhang, Krikamol Muandet, Dino Sejdinovic, Edwin Fong, Siu Lun Chau

arXiv AI

Jun 24

A Survey on Federated Causal Discovery and Inference

arXiv:2606. 23741v1 Announce Type: cross Abstract: Causal reasoning, which encompasses the discovery of causal structures and the inference of causal effects, is fundamental to data-driven decision making.

By Xianjie Guo, Yuwei Wang, Guodu Xiang, Xiaoli Tang, Kui Yu, Han Yu, Qiang Yang

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arXiv Machine Learning

Jul 27

Learning Bidirectional Causal Interactions with Heteroscedastic Neural Networks

arXiv:2607. 22313v1 Announce Type: cross Abstract: Estimating contemporaneous bidirectional interactions from observational data is difficult because each outcome is endogenous to the other, while flexible regressions may capture only reduced-form dependence.

By Masahiro Tanaka

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arXiv Machine Learning

Jun 3

Learning Temporal Causal Structure via Smooth Differentiable Optimization

arXiv:2606. 03227v1 Announce Type: new Abstract: Causal discovery with instantaneous effects in multivariate time series is challenging, as the instantaneous structure must be acyclic.

By Tong Zhao, Ce Guo, Wayne Luk, Emil Lupu, Ray Dipojjwal

benchmarks

arXiv Machine Learning

5d ago

Doubly Robust Estimation of Causal Effect on CVR with Targeted Regularization

arXiv:2608. 13461v1 Announce Type: new Abstract: Post-click conversion rate (CVR) is a key metric in various scenarios including e-commerce and advertising, reflecting the efficiency and user experience in the second stage of the conversion process.

By Jiayi Dan, Bo Li, Lu Deng, Yong Wang

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arXiv Machine Learning

Jun 30

Multiply Robust Causal Mediation Analysis with Continuous Treatments

arXiv:2105. 09254v4 Announce Type: replace-cross Abstract: In many applications, researchers are interested in the direct and indirect causal effects of a treatment or exposure on an outcome of interest.

By Yizhen Xu, AmirEmad Ghassami, Numair Sani, Ilya Shpitser

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Instrumental and Proximal Causal Inference with Gaussian Processes

A Survey on Federated Causal Discovery and Inference

Learning Bidirectional Causal Interactions with Heteroscedastic Neural Networks

Learning Temporal Causal Structure via Smooth Differentiable Optimization

Doubly Robust Estimation of Causal Effect on CVR with Targeted Regularization

Multiply Robust Causal Mediation Analysis with Continuous Treatments