Cover Image

Collective Counterfactual Explanations: Balancing Individual Goals and Collective Dynamics

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ehyaei, Ahmad-Reza, Shirali, Ali, Samadi, Samira
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Wasserstein Distributionally Robust Optimization Through the Lens of Structural Causal Models and Individual Fairness
by: Ehyaei, Ahmad-Reza, et al.
Published: (2025)

Causal Fair Metric: Bridging Causality, Individual Fairness, and Adversarial Robustness
by: Ehyaei, Ahmad-Reza, et al.
Published: (2023)

From Fragile to Certified: Wasserstein Audits of Group Fairness Under Distribution Shift
by: Ehyaei, Ahmad-Reza, et al.
Published: (2025)

Designing Ambiguity Sets for Distributionally Robust Optimization Using Structural Causal Optimal Transport
by: Ehyaei, Ahmad-Reza, et al.
Published: (2025)

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

Flexible Counterfactual Explanations with Generative Models
by: Hellemans, Stig, et al.
Published: (2025)

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

Probabilistically Plausible Counterfactual Explanations with Normalizing Flows
by: Wielopolski, Patryk, et al.
Published: (2024)

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

FACEGroup: Feasible and Actionable Counterfactual Explanations for Group Fairness
by: Fragkathoulas, Christos, et al.
Published: (2024)

Joint Distribution-Informed Shapley Values for Sparse Counterfactual Explanations
by: You, Lei, et al.
Published: (2024)

Axiomatic Foundations of Counterfactual Explanations
by: Amgoud, Leila, et al.
Published: (2026)

CoLa-DCE -- Concept-guided Latent Diffusion Counterfactual Explanations
by: Motzkus, Franz, et al.
Published: (2024)

Unifying Perspectives: Plausible Counterfactual Explanations on Global, Group-wise, and Local Levels
by: Furman, Oleksii, et al.
Published: (2024)

Kernel Treatment Effects with Adaptively Collected Data
by: Zenati, Houssam, et al.
Published: (2025)

Counterfactual Explanations for Model Ensembles Using Entropic Risk Measures
by: Noorani, Erfaun, et al.
Published: (2025)

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

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

DFW: A Novel Weighting Scheme for Covariate Balancing and Treatment Effect Estimation
by: Khan, Ahmad Saeed, et al.
Published: (2025)

Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects Estimation
by: Chauhan, Vinod Kumar, et al.
Published: (2023)

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

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)

Optimizing Input Data Collection for Ranking and Selection
by: Song, Eunhye, et al.
Published: (2025)

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

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

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

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

Benchmark of Likelihood-Free Inference Methods based on Neural and Optimal Transport Approaches
by: Aka, Samira, et al.
Published: (2026)

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

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

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

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

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)

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

The Role of Learning Algorithms in Collective Action
by: Ben-Dov, Omri, et al.
Published: (2024)

CFLight: Enhancing Safety with Traffic Signal Control through Counterfactual Learning
by: Li, Mingyuan, et al.
Published: (2025)

Fairness for the People, by the People: Minority Collective Action
by: Ben-Dov, Omri, et al.
Published: (2025)