A naukri.com initiative
Arxiv
1d
102
Image Credit: Arxiv
Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference
- Two neural network approaches have been developed to approximate the solutions of conditional optimal transport (COT) problems.
- The approaches enable conditional sampling and density estimation, which are important in Bayesian inference.
- The methods represent the target conditional distribution as a transformation of a tractable reference distribution.
- The algorithms use neural networks to parameterize candidate maps and exploit the structure of the COT problem.
Read Full Article
6 Likes
For uninterrupted reading, download the app