Statistical Inference via Generative Models: Flow Matching and Causal Inference
https://arxiv.org/abs/2603.09009
LeapFactual: Reliable Visual Counterfactual Explanation Using Conditional Flow Matching
https://github.com/caicairay/LeapFactual
Probabilistic Modelling is Sufficient for Causal Inference
https://arxiv.org/abs/2512.23408
Causal Inference: A Tale of Three Frameworks
https://arxiv.org/abs/2511.21516
Executable Counterfactuals: Improving LLMs' Causal Reasoning Through Code
https://arxiv.org/abs/2510.01539v1
Executable Counterfactuals: Improving LLMs' Causal Reasoning Through Code
https://arxiv.org/abs/2510.01539v1
Causal AI Scientist
https://zhijing-jin.com/home
https://drive.google.com/file/d/1RWKlAOLgExB22plsH6XAFz_uSpJzOblL/
Combinatorial prediction of therapeutic perturbations using causally-inspired neural networks
https://github.com/mims-harvard/PDGrapher
Efficient Causal Graph Discovery Using Large Language Models
https://arxiv.org/abs/2402.01207
CausalGraph2LLM: Evaluating LLMs for Causal Queries
https://github.com/ivaxi0s/CausalGraph2LLM
Harnessing the Power of Knowledge Graphs to Improve Causal Discovery
https://ieeexplore.ieee.org/document/10916810