Neural Structure Learning with Stochastic Differential Equations.
Benjie WangJoel JenningsWenbo GongPublished in: CoRR (2023)
Keyphrases
- structure learning
- stochastic differential equations
- bayesian networks
- graphical models
- maximum a posteriori estimation
- conditional independence
- brownian motion
- parameter estimation
- transfer learning
- additive gaussian noise
- sample size
- network structure
- markov networks
- dynamic bayesian networks
- probabilistic model
- fractional brownian motion
- belief propagation
- random variables
- differential equations
- least squares
- reinforcement learning