Causal Machine Learning

CML

Improves model interpretability and robustness by identifying causal relationships.

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51015

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Linear Causal Discovery with Interventional Constraints Zhigao Guo Feng Dong CML 3 0 0 30 Oct 2025
A Unified Theory for Causal Inference: Direct Debiased Machine Learning via Bregman-Riesz Regression Masahiro Kato CML 0 0 0 30 Oct 2025
Assessment of the conditional exchangeability assumption in causal machine learning models: a simulation study Gerard T. Portela Jason B. Gibbons Sebastian Schneeweiss Rishi J. Desai CML 2 0 0 30 Oct 2025
Bridging the Gap between Empirical Welfare Maximization and Conditional Average Treatment Effect Estimation in Policy Learning Masahiro Kato OffRL CML 4 0 0 30 Oct 2025
Representation-Level Counterfactual Calibration for Debiased Zero-Shot Recognition Pei Peng MingKun Xie Hang Hao Tong Jin ShengJun Huang BDL CML 2 0 0 30 Oct 2025
The Information-Theoretic Imperative: Compression and the Epistemic Foundations of Intelligence Christian Dittrich Jennifer Flygare Kinne CML 55 0 0 29 Oct 2025
An Analysis of Causal Effect Estimation using Outcome Invariant Data Augmentation Uzair Akbar Niki Kilbertus Hao Shen Krikamol Muandet Bo Dai CML 61 0 0 29 Oct 2025
Causal-Aware Generative Adversarial Networks with Reinforcement Learning T. Nguyen D. Nguyen Tri-Nhan Vo T. Le Sunil Gupta GAN CML 44 0 0 28 Oct 2025
Graph Distance Based on Cause-Effect Estimands with Latents Zhufeng Li Niki Kilbertus CML 65 0 0 28 Oct 2025
Causal Ordering for Structure Learning From Time Series Pedro Sanchez Damian Machlanski Steven McDonagh Sotirios A. Tsaftaris CML AI4TS 4 0 0 28 Oct 2025
Direct Debiased Machine Learning via Bregman Divergence Minimization Masahiro Kato CML 64 1 0 27 Oct 2025
Causal Deep Q Network Elouanes Khelifi A. Saki U. Faghihi CML 69 0 0 27 Oct 2025
Decentralized Causal Discovery using Judo Calculus Sridhar Mahadevan CML 3 0 0 27 Oct 2025
Semi-Supervised Learning under General Causal ModelsIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024 Archer Moore Heejung Shim Jingge Zhu Mingming Gong CML 13 3 0 26 Oct 2025
Identification of Causal Direction under an Arbitrary Number of Latent Confounders Wei Chen Linjun Peng Zhiyi Huang Haoyue Dai Zhifeng Hao Ruichu Cai Kun Zhang CML 12 0 0 26 Oct 2025
MetaCaDI: A Meta-Learning Framework for Scalable Causal Discovery with Unknown Interventions Hans Jarett Ong Yoichi Chikahara Tomoharu Iwata CML BDL 10 0 0 25 Oct 2025
Bridging Prediction and Attribution: Identifying Forward and Backward Causal Influence Ranges Using Assimilative Causal Inference Marios Andreou Nan Chen CML 12 0 0 24 Oct 2025
Estimating Treatment Effects in Networks using Domain Adversarial Training Daan Caljon Jente Van Belle Wouter Verbeke CML 14 0 0 24 Oct 2025
Confounding Robust Deep Reinforcement Learning: A Causal Approach Mingxuan Li Junzhe Zhang Elias Bareinboim OffRL CML 16 0 0 24 Oct 2025
From Black-box to Causal-box: Towards Building More Interpretable Models Inwoo Hwang Yushu Pan Elias Bareinboim CML OOD 63 2 0 24 Oct 2025
Differentiable Constraint-Based Causal Discovery Jincheng Zhou Mengbo Wang Anqi He Yumeng Zhou Hessam Olya Murat Kocaoglu Bruno Ribeiro CML 14 0 0 24 Oct 2025
CausalRec: A CausalBoost Attention Model for Sequential Recommendation Yunbo Hou Tianle Yang Ruijie Li Li He Liang Wang Weiping Li Bo Zheng Guojie Song CML HAI 56 0 0 24 Oct 2025
Towards Error-Centric Intelligence II: Energy-Structured Causal Models Marcus Thomas CML 12 0 0 24 Oct 2025
Causal Debiasing for Visual Commonsense ReasoningIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2025 Jiayi Zou Gengyun Jia Bing-Kun Bao CML 12 2 0 23 Oct 2025
Neural Networks for Censored Expectile Regression Based on Data Augmentation Wei Cao Shanshan Wang CML 12 0 0 23 Oct 2025
Competition is the key: A Game Theoretic Causal Discovery Approach Amartya Roy Souvik Chakraborty CML 15 0 0 23 Oct 2025
ROPES: Robotic Pose Estimation via Score-Based Causal Representation Learning Pranamya Kulkarni Puranjay Datta Burak Varıcı Emre Acartürk Karthikeyan Shanmugam A. Tajer CML 34 0 0 23 Oct 2025
Identification and Debiased Learning of Causal Effects with General Instrumental Variables Shuyuan Chen Peng Zhang Yifan Cui CML 12 0 0 23 Oct 2025
DARE: A Deformable Adaptive Regularization Estimator for Learning-Based Medical Image Registration Ahsan Raza Siyal Markus Haltmeier R. Steiger Malik Galijasevic E. Gizewski A. E. Grams OOD MedIm CML 60 0 0 22 Oct 2025
Throwing Vines at the Wall: Structure Learning via Random Search Thibault Vatter Thomas Nagler CML 43 0 0 22 Oct 2025
Inference on Local Variable Importance Measures for Heterogeneous Treatment Effects Pawel Morzywolek Peter B. Gilbert Alex Luedtke CML 33 0 0 21 Oct 2025
Improving the Generation and Evaluation of Synthetic Data for Downstream Medical Causal Inference Harry Amad Zhaozhi Qian Dennis Frauen Julianna Piskorz Stefan Feuerriegel Mihaela van der Schaar CML 35 1 0 21 Oct 2025
Towards Identifiability of Hierarchical Temporal Causal Representation Learning Zijian Li Minghao Fu Junxian Huang Yifan Shen Ruichu Cai Yuewen Sun Guangyi Chen Kun Zhang CML 92 0 0 21 Oct 2025
CausalMamba: Scalable Conditional State Space Models for Neural Causal Inference Sangyoon Bae Jiook Cha Mamba CML AI4CE 21 0 0 20 Oct 2025
OG-Rank: Learning to Rank Fast and Slow with Uncertainty and Reward-Trend Guided Adaptive Exploration Praphul Singh Corey D Barrett Sumana Srivasta Irfan Bulu Sri Gadde Krishnaram Kenthapadi OffRL BDL CML 16 0 0 20 Oct 2025
Diverse Influence Component Analysis: A Geometric Approach to Nonlinear Mixture Identifiability Hoang-Son Nguyen Xiao Fu CML 38 0 0 19 Oct 2025
On the Granularity of Causal Effect Identifiability Yizuo Chen Adnan Darwiche CML 12 0 0 19 Oct 2025
Graph Learning is Suboptimal in Causal Bandits Mohammad Shahverdikondori Jalal Etesami Negar Kiyavash CML 0 0 0 19 Oct 2025
Realizing LLMs' Causal Potential Requires Science-Grounded, Novel Benchmarks Ashutosh Srivastava Lokesh Nagalapatti Gautam Jajoo Aniket Vashishtha Parameswari Krishnamurthy Amit Sharma CML 27 0 0 18 Oct 2025
Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection Dongchan Cho Jiho Han Keumyeong Kang Minsang Kim Honggyu Ryu Namsoon Jung AI4TS CML 12 0 0 18 Oct 2025
Kernel Regression in Structured Non-IID Settings: Theory and Implications for Denoising Score Learning Dechen Zhang Zhenmei Shi Yi Zhang Yingyu Liang Difan Zou CML 12 0 0 17 Oct 2025
Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift Emam Hossain Muhammad Hasan Ferdous Devon Dunmire Aneesh Subramanian Md. Osman Gani OOD CML 28 0 0 17 Oct 2025
Learning density ratios in causal inference using Bregman-Riesz regression Oliver J. Hines Caleb H. Miles CML 12 0 0 17 Oct 2025
Expediting Reinforcement Learning by Incorporating Knowledge About Temporal Causality in the EnvironmentCLEaR (CLEaR), 2025 Jan Corazza Hadi Partovi Aria Daniel Neider Zhe Xu CML 21 7 0 17 Oct 2025
Response to Discussions of "Causal and Counterfactual Views of Missing Data Models" Razieh Nabi Rohit Bhattacharya I. Shpitser J. M. Robins CML 16 0 0 16 Oct 2025
Interaction Concordance Index: Performance Evaluation for Interaction Prediction Methods T. Pahikkala Riikka Numminen P. Movahedi Napsu Karmitsa A. Airola CML 23 0 0 16 Oct 2025
Towards Error Centric Intelligence I, Beyond Observational Learning Marcus A. Thomas CML 12 1 0 16 Oct 2025
Measure-Theoretic Anti-Causal Representation Learning Arman Behnam Binghui Wang OOD CML 24 0 0 16 Oct 2025
Local Causal Discovery for Statistically Efficient Causal Inference Mátyás Schubert Tom Claassen Sara Magliacane CML 19 0 0 16 Oct 2025
From Guess2Graph: When and How Can Unreliable Experts Safely Boost Causal Discovery in Finite Samples? Sujai Hiremath Dominik Janzing P. M. Faller Patrick Blobaum Elke Kirschbaum S. Kasiviswanathan Kyra Gan CML 1 0 0 16 Oct 2025

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