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