Tensor Flow Probability

GPTKB entity

Statements (59)
Predicate Object
gptkbp:instance_of gptkb:Library
gptkbp:based_on gptkb:Graphics_Processing_Unit
gptkbp:developed_by gptkb:Job_Search_Engine
gptkbp:has_community active community
gptkbp:has_documentation https://www.tensorflow.org/probability
gptkbp:has_feature flexibility
performance optimization
scalability
automatic differentiation
custom distributions
support for mobile deployment
support for time series analysis
support for cloud computing
support for data visualization
support for edge computing
support for distributed computing
support for deep learning
support for reinforcement learning
support for model evaluation
support for statistical tests
custom bijectors
easy integration with Tensor Flow models
interoperability with Num Py
modeling complex distributions
support for Bayesian neural networks
support for Bayesian optimization
support for Gaussian processes
support for Tensor Flow datasets
support for empirical Bayes
support for hierarchical models
support for interactive modeling
support for large-scale data analysis
support for latent variable models
support for model selection
support for nonparametric models
support for probabilistic graphical models
support for simulation-based inference
support for uncertainty quantification
support for variational inference
https://www.w3.org/2000/01/rdf-schema#label Tensor Flow Probability
gptkbp:is_a_hub_for https://github.com/tensorflow/probability
gptkbp:is_compatible_with gptkb:Graphics_Processing_Unit
gptkbp:is_used_for gptkb:software_framework
statistical analysis
probabilistic reasoning
gptkbp:language gptkb:Library
gptkbp:provides distributions
probabilistic programming
bijectors
probabilistic layers
gptkbp:release_date gptkb:2018
gptkbp:supports gptkb:Tensor_Flow_2.x
gptkb:Markov_Chain_Monte_Carlo
Bayesian inference
Monte Carlo methods
gptkbp:used_in gptkb:Research_Institute
industry applications
gptkbp:bfsParent gptkb:Graphics_Processing_Unit
gptkbp:bfsLayer 3