Cover Image

CFLight: Enhancing Safety with Traffic Signal Control through Counterfactual Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Mingyuan, Liu, Chunyu, Li, Zhuojun, Liu, Xiao, Yu, Guangsheng, Du, Bo, Shen, Jun, Wu, Qiang
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Advancing Counterfactual Inference through Nonlinear Quantile Regression
by: Xie, Shaoan, et al.
Published: (2023)

DiffusionCounterfactuals: Inferring High-dimensional Counterfactuals with Guidance of Causal Representations
by: Zhu, Jiageng, et al.
Published: (2024)

Teleporter Theory: A General and Simple Approach for Modeling Cross-World Counterfactual Causality
by: Li, Jiangmeng, et al.
Published: (2024)

Counterfactual identifiability beyond global monotonicity: non-monotone triangular structural causal models
by: Tan, Pengcheng, et al.
Published: (2026)

Transformer-Based Spatial-Temporal Counterfactual Outcomes Estimation
by: Li, He, et al.
Published: (2025)

Counterfactual Generative Models for Time-Varying Treatments
by: Wu, Shenghao, et al.
Published: (2023)

Assessing Electricity Service Unfairness with Transfer Counterfactual Learning
by: Wei, Song, et al.
Published: (2023)

Causal Contrastive Learning for Counterfactual Regression Over Time
by: Bouchattaoui, Mouad El, et al.
Published: (2024)

Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression
by: Wu, Anpeng, et al.
Published: (2024)

De-confounding Representation Learning for Counterfactual Inference on Continuous Treatment via Generative Adversarial Network
by: Zhao, Yonghe, et al.
Published: (2023)

Towards Accurate and Interpretable Time-series Forecasting: A Polynomial Learning Approach
by: Liu, Bo, et al.
Published: (2026)

Orthogonal Uplift Learning with Permutation-Invariant Representations for Combinatorial Treatments
by: Su, Xinyan, et al.
Published: (2026)

FuzzyLight: A Robust Two-Stage Fuzzy Approach for Traffic Signal Control Works in Real Cities
by: Li, Mingyuan, et al.
Published: (2025)

Geometry Adaptive Counterfactual Distribution Learning with Diffusion-Guided Smoothing
by: Kim, Kwangho
Published: (2026)

Semiparametric Counterfactual Regression
by: Kim, Kwangho
Published: (2025)

Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing
by: Wang, Jitao, et al.
Published: (2025)

Scalable Counterfactual Risk Estimation for Rare Events in Longitudinal Data
by: Yin, Xiaohui, et al.
Published: (2026)

Relative Counterfactual Contrastive Learning for Mitigating Pretrained Stance Bias in Stance Detection
by: Zhang, Jiarui, et al.
Published: (2024)

No $D_{\text{train}}$: Model-Agnostic Counterfactual Explanations Using Reinforcement Learning
by: Sun, Xiangyu, et al.
Published: (2024)

DoFlow: Flow-based Generative Models for Interventional and Counterfactual Forecasting on Time Series
by: Wu, Dongze, et al.
Published: (2025)

Generally-Occurring Model Change for Robust Counterfactual Explanations
by: Xu, Ao, et al.
Published: (2024)

Feature Matching Intervention: Leveraging Observational Data for Causal Representation Learning
by: Li, Haoze, et al.
Published: (2025)

Representation-Enhanced Neural Knowledge Integration with Application to Large-Scale Medical Ontology Learning
by: Liu, Suqi, et al.
Published: (2024)

DoubleGen: Debiased Generative Modeling of Counterfactuals
by: Luedtke, Alex, et al.
Published: (2025)

Nonparametric Identification and Inference for Counterfactual Distributions with Confounding
by: Sun, Jianle, et al.
Published: (2026)

Causal and Counterfactual Views of Missing Data Models
by: Nabi, Razieh, et al.
Published: (2022)

Constrained Multi-objective Bayesian Optimization through Optimistic Constraints Estimation
by: Li, Diantong, et al.
Published: (2024)

Counterfactual Cocycles: A Framework for Robust and Coherent Counterfactual Transports
by: Dance, Hugh, et al.
Published: (2024)

Deep Deterministic Nonlinear ICA via Total Correlation Minimization with Matrix-Based Entropy Functional
by: Li, Qiang, et al.
Published: (2025)

Watermarking Counterfactual Explanations
by: Guo, Hangzhi, et al.
Published: (2024)

Semiparametric Learning from Open-Set Label Shift Data
by: Liu, Siyan, et al.
Published: (2025)

Two-Stage Data Synthesization: A Statistics-Driven Restricted Trade-off between Privacy and Prediction
by: Liu, Xiaotong, et al.
Published: (2026)

Collective Counterfactual Explanations: Balancing Individual Goals and Collective Dynamics
by: Ehyaei, Ahmad-Reza, et al.
Published: (2024)

Response to Discussions of "Causal and Counterfactual Views of Missing Data Models"
by: Nabi, Razieh, et al.
Published: (2025)

Modeling Causal Mechanisms with Diffusion Models for Interventional and Counterfactual Queries
by: Chao, Patrick, et al.
Published: (2023)

Sequential Conditional Transport on Probabilistic Graphs for Interpretable Counterfactual Fairness
by: Machado, Agathe Fernandes, et al.
Published: (2024)

Towards Characterizing Domain Counterfactuals For Invertible Latent Causal Models
by: Zhou, Zeyu, et al.
Published: (2023)

Learning Continuous Network Emerging Dynamics from Scarce Observations via Data-Adaptive Stochastic Processes
by: Cui, Jiaxu, et al.
Published: (2023)

A Generative Framework for Causal Estimation via Importance-Weighted Diffusion Distillation
by: Song, Xinran, et al.
Published: (2025)

Engression: Extrapolation through the Lens of Distributional Regression
by: Shen, Xinwei, et al.
Published: (2023)