Learning non-Gaussian graphical models via Hessian scores and triangular transport.
Ricardo BaptistaYoussef M. MarzoukRebecca E. MorrisonOlivier ZahmPublished in: CoRR (2021)
Keyphrases
- graphical models
- probabilistic model
- structural learning
- structure learning
- markov logic networks
- bayesian networks
- learning algorithm
- relational dependency networks
- undirected graphical models
- belief propagation
- random variables
- probabilistic inference
- graph structure
- markov networks
- exact inference
- probabilistic graphical models
- loopy belief propagation
- statistical relational learning
- prior knowledge
- optimal solution
- reinforcement learning