arXiv:2009.14393 공식 코드 · Papers with Code

TensorBNN: Bayesian Inference for Neural Networks using Tensorflow

Braden Kronheim, Michelle Kuchera, Harrison Prosper

제출 2020-09-30

원문 초록

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 training features as well as its ability to use modern graphics processing units (GPU) in both the training and prediction stages.

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