Cascade-based Randomization for Inferring Causal Effects under Diffusion Interference
Fuente:
arXiv
Saved in:
| Main Authors: | Fatemi, Zahra, Pouget-Abadie, Jean, Zheleva, Elena |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Inferring Graphs from Cascades: A Sparse Recovery Framework
by: Pouget-Abadie, Jean, et al.
Published: (2015)
by: Pouget-Abadie, Jean, et al.
Published: (2015)
Inferring Individual Direct Causal Effects Under Heterogeneous Peer Influence
by: Adhikari, Shishir, et al.
Published: (2023)
by: Adhikari, Shishir, et al.
Published: (2023)
Learning Exposure Mapping Functions for Inferring Heterogeneous Peer Effects
by: Adhikari, Shishir, et al.
Published: (2025)
by: Adhikari, Shishir, et al.
Published: (2025)
Estimating Causal Effects in Networks with Cluster-Based Bandits
by: Faruk, Ahmed Sayeed, et al.
Published: (2025)
by: Faruk, Ahmed Sayeed, et al.
Published: (2025)
Inferring Diffusion Structures of Heterogeneous Network Cascade
by: Yuan, Yubai, et al.
Published: (2025)
by: Yuan, Yubai, et al.
Published: (2025)
Leveraging heterogeneous spillover in maximizing contextual bandit rewards
by: Faruk, Ahmed Sayeed, et al.
Published: (2023)
by: Faruk, Ahmed Sayeed, et al.
Published: (2023)
Learning Peer Influence Probabilities with Linear Contextual Bandits
by: Faruk, Ahmed Sayeed, et al.
Published: (2025)
by: Faruk, Ahmed Sayeed, et al.
Published: (2025)
Predicting Cascading Failures with a Hyperparametric Diffusion Model
by: Xiang, Bin, et al.
Published: (2024)
by: Xiang, Bin, et al.
Published: (2024)
Learning Individual Treatment Effects under Heterogeneous Interference in Networks
by: Zhao, Ziyu, et al.
Published: (2022)
by: Zhao, Ziyu, et al.
Published: (2022)
Policy Targeting under Network Interference
by: Viviano, Davide
Published: (2019)
by: Viviano, Davide
Published: (2019)
The Effects of Randomness on the Stability of Node Embeddings
by: Schumacher, Tobias, et al.
Published: (2020)
by: Schumacher, Tobias, et al.
Published: (2020)
Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects
by: Khatami, Seyedeh Baharan, et al.
Published: (2024)
by: Khatami, Seyedeh Baharan, et al.
Published: (2024)
Random Walk Diffusion for Efficient Large-Scale Graph Generation
by: Bernecker, Tobias, et al.
Published: (2024)
by: Bernecker, Tobias, et al.
Published: (2024)
Optimizing Treatment Allocation in the Presence of Interference
by: Caljon, Daan, et al.
Published: (2024)
by: Caljon, Daan, et al.
Published: (2024)
Differences-in-Neighbors for Network Interference in Experiments
by: Peng, Tianyi, et al.
Published: (2025)
by: Peng, Tianyi, et al.
Published: (2025)
Improving the Variance of Differentially Private Randomized Experiments through Clustering
by: Javanmard, Adel, et al.
Published: (2023)
by: Javanmard, Adel, et al.
Published: (2023)
Using LLMs to Infer Non-Binary COVID-19 Sentiments of Chinese Micro-bloggers
by: Hu, Jerry Chongyi, et al.
Published: (2025)
by: Hu, Jerry Chongyi, et al.
Published: (2025)
CausalMamba: Interpretable State Space Modeling for Temporal Rumor Causality
by: Zhan, Xiaotong, et al.
Published: (2025)
by: Zhan, Xiaotong, et al.
Published: (2025)
Beyond Leakage and Complexity: Towards Realistic and Efficient Information Cascade Prediction
by: Peng, Jie, et al.
Published: (2025)
by: Peng, Jie, et al.
Published: (2025)
Scalable Deep Graph Clustering with Random-walk based Self-supervised Learning
by: Li, Xiang, et al.
Published: (2021)
by: Li, Xiang, et al.
Published: (2021)
Diffusion-based Negative Sampling on Graphs for Link Prediction
by: Nguyen, Trung-Kien, et al.
Published: (2024)
by: Nguyen, Trung-Kien, et al.
Published: (2024)
On Evolution-Based Models for Experimentation Under Interference
by: Shirani, Sadegh, et al.
Published: (2025)
by: Shirani, Sadegh, et al.
Published: (2025)
Graph Representation Learning via Causal Diffusion for Out-of-Distribution Recommendation
by: Zhao, Chu, et al.
Published: (2024)
by: Zhao, Chu, et al.
Published: (2024)
HetCAN: A Heterogeneous Graph Cascade Attention Network with Dual-Level Awareness
by: Zhao, Zeyuan, et al.
Published: (2023)
by: Zhao, Zeyuan, et al.
Published: (2023)
A Two-Part Machine Learning Approach to Characterizing Network Interference in A/B Testing
by: Yuan, Yuan, et al.
Published: (2023)
by: Yuan, Yuan, et al.
Published: (2023)
CasCIFF: A Cross-Domain Information Fusion Framework Tailored for Cascade Prediction in Social Networks
by: Zhu, Hongjun, et al.
Published: (2023)
by: Zhu, Hongjun, et al.
Published: (2023)
Graph Out-of-Distribution Generalization via Causal Intervention
by: Wu, Qitian, et al.
Published: (2024)
by: Wu, Qitian, et al.
Published: (2024)
Graph Contrastive Invariant Learning from the Causal Perspective
by: Mo, Yanhu, et al.
Published: (2024)
by: Mo, Yanhu, et al.
Published: (2024)
Causality-Driven Disentangled Representation Learning in Multiplex Graphs
by: Nasiri, Saba, et al.
Published: (2026)
by: Nasiri, Saba, et al.
Published: (2026)
Node Classification in Random Trees
by: Nuijten, Wouter W. L., et al.
Published: (2023)
by: Nuijten, Wouter W. L., et al.
Published: (2023)
Don't Forget to Connect! Improving RAG with Graph-based Reranking
by: Dong, Jialin, et al.
Published: (2024)
by: Dong, Jialin, et al.
Published: (2024)
Mitigating Cascading Effects in Large Adversarial Graph Environments
by: Cunningham, James D., et al.
Published: (2024)
by: Cunningham, James D., et al.
Published: (2024)
Efficient Heterogeneous Graph Learning via Random Projection
by: Hu, Jun, et al.
Published: (2023)
by: Hu, Jun, et al.
Published: (2023)
Jointly Optimizing Debiased CTR and Uplift for Coupons Marketing: A Unified Causal Framework
by: Yang, Siyun, et al.
Published: (2026)
by: Yang, Siyun, et al.
Published: (2026)
Hub-aware Random Walk Graph Embedding Methods for Classification
by: Tomčić, Aleksandar, et al.
Published: (2022)
by: Tomčić, Aleksandar, et al.
Published: (2022)
Faster Local Solvers for Graph Diffusion Equations
by: Bai, Jiahe, et al.
Published: (2024)
by: Bai, Jiahe, et al.
Published: (2024)
Efficient Identity and Position Graph Embedding via Spectral-Based Random Feature Aggregation
by: Qin, Meng, et al.
Published: (2025)
by: Qin, Meng, et al.
Published: (2025)
Leveraging Non-linear Dimension Reduction and Random Walk Co-occurrence for Node Embedding
by: DeWolfe, Ryan
Published: (2026)
by: DeWolfe, Ryan
Published: (2026)
Graph-based Diffusion Model for Collaborative Filtering
by: Zhang, Xuan, et al.
Published: (2025)
by: Zhang, Xuan, et al.
Published: (2025)
Unifying Generation and Prediction on Graphs with Latent Graph Diffusion
by: Zhou, Cai, et al.
Published: (2024)
by: Zhou, Cai, et al.
Published: (2024)
Similar Items
-
Inferring Graphs from Cascades: A Sparse Recovery Framework
by: Pouget-Abadie, Jean, et al.
Published: (2015) -
Inferring Individual Direct Causal Effects Under Heterogeneous Peer Influence
by: Adhikari, Shishir, et al.
Published: (2023) -
Learning Exposure Mapping Functions for Inferring Heterogeneous Peer Effects
by: Adhikari, Shishir, et al.
Published: (2025) -
Estimating Causal Effects in Networks with Cluster-Based Bandits
by: Faruk, Ahmed Sayeed, et al.
Published: (2025) -
Inferring Diffusion Structures of Heterogeneous Network Cascade
by: Yuan, Yubai, et al.
Published: (2025)