Tag: probabilistic-ml
Concepts
- Aleatoric vs Epistemic Uncertainty
- Amortized Inference and Encoder Networks
- Baum-Welch and Forward-Backward Inference
- Bayes by Backprop
- Deep Ensembles for Uncertainty Estimation
- Deep Kernel Learning
- Denoising Diffusion Probabilistic Models
- The Evidence Lower Bound
- Evidential Deep Learning
- The Exponential Family and Natural Parameters
- Gaussian Process Classification
- Generative vs Discriminative Models
- The Laplace Approximation for Neural Networks
- Latent Variable Models and the ELBO
- Markov Random Fields and Factor Graphs
- Probabilistic Graphical Models
- Sparse Gaussian Processes and Inducing Points
- SWAG: Stochastic Weight Averaging-Gaussian
- The Reparameterization Trick
- Variable Elimination for Exact Inference