Causal Inference using Gaussian Processes with Structured Latent Confounders.
Sam WittyKenta TakatsuDavid D. JensenVikash MansinghkaPublished in: ICML (2020)
Keyphrases
- gaussian processes
- causal inference
- observational data
- latent variables
- gaussian process
- experimental data
- random variables
- additive noise
- probabilistic model
- discrete data
- approximate inference
- causal models
- hyperparameters
- nonmonotonic reasoning
- topic models
- abductive reasoning
- prior knowledge
- feature selection
- edge detection
- image segmentation
- causal discovery
- bayesian networks
- learning algorithm
- image reconstruction
- sample size
- em algorithm
- maximum likelihood