TensorBNN: Bayesian inference for neural networks using TensorFlow
We report that TensorBNN is a new package based on TensorFlow that implements Bayesian inference for modern neural network models. The posterior density of neural network model parameters is represented as a point cloud sampled using Hamiltonian Monte Carlo. The TensorBNN package leverages TensorFlow's architecture and its ability to use modern graphics processing units in both the training and prediction stages.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗