Causal Approach

Causal approaches in machine learning aim to move beyond simple correlations, focusing instead on understanding and modeling the underlying causal relationships within data. Current research emphasizes developing methods to identify causal structures, particularly in complex domains like biology and social sciences, often employing techniques like causal Bayesian networks, do-calculus, and causal forests, alongside large language models for knowledge integration. This focus on causality enhances model robustness, generalizability, and interpretability, leading to more reliable predictions and fairer decision-making across diverse applications, from healthcare and finance to software engineering and industrial troubleshooting.

Papers

October 29, 2024

CausAdv: A Causal-based Framework for Detecting Adversarial Examples
Hichem Debbi
Adversarial Example Adversarial Robustness Adversarial Perturbation Adversarial Text Causal Feature Causal Approach

October 25, 2024

Language Agents Meet Causality -- Bridging LLMs and Causal World Models
John Gkountouras, Matthias Lindemann, Phillip Lippe, Efstratios Gavves, Ivan Titov
Large Language Model Causal Representation Learning Causal Language Causal Knowledge Causal Approach Causal Interpretation Causal World Model

October 4, 2024

Predicting perturbation targets with causal differential networks
Menghua Wu, Umesh Padia, Sean H. Murphy, Regina Barzilay, Tommi Jaakkola
Causal Discovery Causal Graph Causal Discovery Algorithm Causal Approach Causal Network Targeted Perturbation

September 15, 2024

A Survey of Out-of-distribution Generalization for Graph Machine Learning from a Causal View
Jing Ma
Timely Survey Distribution Generalization Graph Machine Learning Causal Approach Causal View Graph Generalization

July 30, 2024

Industrial-Grade Smart Troubleshooting through Causal Technical Language Processing: a Proof of Concept
Alexandre Trilla, Ossee Yiboe, Nenad Mijatovic, Jordi Vitrià
Causal Relationship High Impact Concept Causal Learning Predictive Maintenance Partial Proof Causal Approach Causal Explanation Causal Machine Intelligent Fault Diagnosis

May 18, 2024

Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model
Chenyin Gao, Zhiming Zhang, Shu Yang
Causal Model Causal Approach Churn Prediction Block Model Customer Churn

May 15, 2024

Enhancing Airline Customer Satisfaction: A Machine Learning and Causal Analysis Approach
Tejas Mirthipati
Machine Learning Causal Inference Causal Approach User Satisfaction Customer Experience

February 2, 2024

Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach
Masayuki Takayama, Tadahisa Okuda, Thong Pham, Tatsuyoshi Ikenoue, Shingo Fukuma, Shohei Shimizu, Akiyoshi Sannai
Causal Inference Causal Discovery Causal Model Causal Approach

December 20, 2023

Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach
Wen Huang, Xintao Wu
Bandit Algorithm Regret Analysis Causal Approach Systematic Bias Causal Constraint Offline Dataset Contextual Bandit Setting

December 15, 2023

Diagnosing and Rectifying Fake OOD Invariance: A Restructured Causal Approach
Ziliang Chen, Yongsen Zheng, Zhao-Rong Lai, Quanlong Guan, Liang Lin
Medical Diagnosis Invariant Representation Causal Feature Causal Approach Invariant Causal Feature

November 5, 2023

CausalCite: A Causal Formulation of Paper Citations
Ishan Kumar, Zhijing Jin, Ehsan Mokhtarian, Siyuan Guo, Yuen Chen, Mrinmaya Sachan, Bernhard Schölkopf
Causal Effect Causal Approach Multiple Citation

October 12, 2023

October 10, 2023

Benchmarking and Explaining Large Language Model-based Code Generation: A Causality-Centric Approach
Zhenlan Ji, Pingchuan Ma, Zongjie Li, Shuai Wang
Large Language Model Code Generation Causal Graph Benchmark Platform Causal Approach LLM Generated Code Causality Analysis

September 13, 2023

MCNS: Mining Causal Natural Structures Inside Time Series via A Novel Internal Causality Scheme
Yuanhao Liu, Dehui Du, Zihan Jiang, Anyan Huang, Yiyang Li
Causal Inference Causal Graph Causal Structure Causal Structure Learning Causal Approach

June 15, 2023

PEACE: Cross-Platform Hate Speech Detection- A Causality-guided Framework
Paras Sheth, Tharindu Kumarage, Raha Moraffah, Aman Chadha, Huan Liu
Hate Speech Hate Speech Detection Hateful Content Causal Approach Hate Speech Detection Model

June 8, 2023

Reconciling Predictive and Statistical Parity: A Causal Approach
Drago Plecko, Elias Bareinboim
Fair Machine Learning Fairness Notion Causal Approach Fairness Measure Statistical Parity

May 28, 2023

Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach
Yudi Zhang, Yali Du, Biwei Huang, Ziyan Wang, Jun Wang, Meng Fang, Mykola Pechenizkiy
Reinforcement Learning Causal Approach Markovian Reward Reward Redistribution

May 23, 2023

FITNESS: A Causal De-correlation Approach for Mitigating Bias in Machine Learning Software
Ying Xiao, Shangwen Wang, Sicen Liu, Dingyuan Xue, Xian Zhan, Yepang Liu
Bias Mitigation Mitigating Bias Biased Datasets Physical Activity Causal Approach Fairness Performance Trade Machine Learning Software

May 17, 2023

Risk Assessment of Lymph Node Metastases in Endometrial Cancer Patients: A Causal Approach
Alessio Zanga, Alice Bernasconi, Peter J. F. Lucas, Hanny Pijnenborg, Casper Reijnen, Marco Scutari, Fabio Stella
Risk Assessment Causal Discovery Algorithm Causal Approach Lymph Node Causal Bayesian Network

Causal Approach

Papers

CausAdv: A Causal-based Framework for Detecting Adversarial Examples

Language Agents Meet Causality -- Bridging LLMs and Causal World Models

Predicting perturbation targets with causal differential networks

A Survey of Out-of-distribution Generalization for Graph Machine Learning from a Causal View

Industrial-Grade Smart Troubleshooting through Causal Technical Language Processing: a Proof of Concept

Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model

Enhancing Airline Customer Satisfaction: A Machine Learning and Causal Analysis Approach

Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach

Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach

Diagnosing and Rectifying Fake OOD Invariance: A Restructured Causal Approach

CausalCite: A Causal Formulation of Paper Citations

Machine Learning Who to Nudge: Causal vs Predictive Targeting in a Field Experiment on Student Financial Aid Renewal

Towards Causal Deep Learning for Vulnerability Detection

Benchmarking and Explaining Large Language Model-based Code Generation: A Causality-Centric Approach

MCNS: Mining Causal Natural Structures Inside Time Series via A Novel Internal Causality Scheme

PEACE: Cross-Platform Hate Speech Detection- A Causality-guided Framework

Reconciling Predictive and Statistical Parity: A Causal Approach

Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach

FITNESS: A Causal De-correlation Approach for Mitigating Bias in Machine Learning Software

Risk Assessment of Lymph Node Metastases in Endometrial Cancer Patients: A Causal Approach