Variational Inference and the Reparameterization Trick
GPTKB entity
Statements (65)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:academic_journals
|
| gptkbp:application |
gptkb:Deep_Learning
|
| gptkbp:author |
gptkb:D._P._Kingma
gptkb:M._Welling |
| gptkbp:concept |
Variational Inference
Reparameterization Trick |
| gptkbp:field |
gptkb:machine_learning
Bayesian Inference |
| https://www.w3.org/2000/01/rdf-schema#label |
Variational Inference and the Reparameterization Trick
|
| gptkbp:impact |
Probabilistic Models
Latent Variable Models |
| gptkbp:published_in |
Proceedings of the 31st International Conference on Machine Learning
|
| gptkbp:related_to |
gptkb:servers
gptkb:Tensor_Flow gptkb:Artificial_Intelligence gptkb:Model gptkb:cloud_computing gptkb:neural_networks gptkb:Hyperparameter_Tuning gptkb:machine_learning gptkb:Big_Data gptkb:Py_Torch gptkb:Data_Science gptkb:Data_Visualization gptkb:Bayesian_Neural_Networks gptkb:Markov_Chain_Monte_Carlo Cross-Validation Data Analysis Data Mining Data Preprocessing Feature Learning Parallel Computing Performance Metrics Posterior Distribution Research Methodology Statistical Inference Supervised Learning Unsupervised Learning Algorithmic Efficiency Computational Complexity Information Theory Scientific Computing Optimization Techniques Model Evaluation Algorithm Development Feature Engineering Model Selection Deep Learning Frameworks Generative Models Monte Carlo Methods Statistical Learning Statistical Tests Computational Statistics Representation Learning Evaluation Methods Machine Learning Theory Inference Algorithms Approximate Inference Latent Variable Inference Variational Distribution |
| gptkbp:technique |
gptkb:Variational_Autoencoders
Stochastic Gradient Variational Bayes |
| gptkbp:year |
gptkb:2014
|
| gptkbp:bfsParent |
gptkb:D._P._Kingma
|
| gptkbp:bfsLayer |
5
|