Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification
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Updated
Aug 4, 2020 - Python
Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification
Uncertainty Quantification of RANS Data-Driven Turbulence Modeling
This is the code repository for the DuSt-MPC paper, published at Robotics: Science and Systems (RSS) 2021.
PyTorch implementation of Stein Variational Gradient Descent
Python and MATLAB code for Stein Variational sampling methods
TensorFlow Implementation of Stein Variational Gradient Descent (SVGD)
Learning to draw samples: with application to amortized maximum likelihood estimator for generative adversarial learning
SVGD to the quantum setting. Crowdfund: $QUANTUM: Prof. Ferrie
A pytorch implementation of Amortized Stein Variational Gradient Descent/ Stein GAN
An implementation of SVGD in PyTorch
Implementation of Stein Variational Gradient Descent with TensorFlow 2.0
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