SVI-DAG: A Structured Variational Inference Approach to Bayesian Causal Discovery
Shrenik Zinage
cs.LG, cs.AI
Submitted: 2026-08-23
Updated: 2026-08-25
Code: https://github.com/shrenikvz/SVI-DAG
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Ranking via Sinkhorn Propagation
- Variational Causal Networks: Approximate Bayesian Inference over Causal Structures
- Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path?
- International AI Safety Report 2026
- A Meta-Learning Approach to Bayesian Causal Discovery
- Categorical Reparameterization with Gumbel-Softmax
- Adam: A Method for Stochastic Optimization
- Gradient-Based Neural DAG Learning
- The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
- A Graph Autoencoder Approach to Causal Structure Learning
- Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes
- ProDAG: Projected Variational Inference for Directed Acyclic Graphs
- Differentiable Constraint-Based Causal Discovery
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