Node Intervention

Node intervention, a crucial aspect of causal inference, aims to identify causal relationships within complex systems by strategically manipulating individual or groups of nodes and observing the resulting changes. Current research focuses on developing algorithms, often employing deep reinforcement learning or leveraging score functions, to efficiently design and interpret interventions, particularly in scenarios involving multiple simultaneously manipulated nodes and unknown intervention targets. This work is significant because it enables more accurate causal discovery from observational and interventional data, with applications ranging from gene regulation analysis to optimizing complex systems like traffic flow or disease control.

Papers

October 31, 2024

Learning Mixtures of Unknown Causal Interventions
Abhinav Kumar, Kirankumar Shiragur, Caroline Uhler
Causal Graph Causal Direction Learning Mixture Markov Equivalence Class Interventional Data Node Intervention

June 9, 2024

Linear Causal Representation Learning from Unknown Multi-node Interventions
Burak Varıcı, Emre Acartürk, Karthikeyan Shanmugam, Ali Tajer
Causal Representation Learning Latent Causal Causal Representation Node Intervention

May 26, 2024

Amortized Active Causal Induction with Deep Reinforcement Learning
Yashas Annadani, Panagiotis Tigas, Stefan Bauer, Adam Foster
Deep Reinforcement Learning Intervention Policy Active Causal Node Intervention

November 5, 2023

Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions
Simon Bing, Urmi Ninad, Jonas Wahl, Jakob Runge
Causal Representation Learning Latent Causal Ground Truth Causal Node Intervention

October 6, 2023

Amortized Network Intervention to Steer the Excitatory Point Processes
Zitao Song, Wendi Ren, Shuang Li
Model Based Reinforcement Learning Dynamic Graph Hidden Dynamic Node Intervention

May 8, 2023

New metrics and search algorithms for weighted causal DAGs
Davin Choo, Kirankumar Shiragur
Causal Graph Causal Relationship Parameter Update Search Algorithm New Metric Causal DAG Node Intervention

October 1, 2022

Disentangling Mixtures of Unknown Causal Interventions
Abhinav Kumar, Gaurav Sinha
Partial Identifiability Learning Mixture Mixture Weight Causal Bayesian Network Genetic Perturbation Node Intervention Unknown Intervention

November 9, 2021

Universal Lower Bound for Learning Causal DAGs with Atomic Interventions
Vibhor Porwal, Piyush Srivastava, Gaurav Sinha
Lower Bound Synthetic Graph Markov Equivalence Class Causal DAG Node Intervention