karlnapf / kernel_goodness_of_fitLinks
Code for the paper "A Kernel Test of Goodness of Fit" by Kacper Chwialkowski, Heiko Strathmann, Arthur Gretton
☆24Updated 9 years ago
Alternatives and similar repositories for kernel_goodness_of_fit
Users that are interested in kernel_goodness_of_fit are comparing it to the libraries listed below
Sorting:
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 5 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆63Updated 7 years ago
- gpbo☆25Updated 4 years ago
- ☆12Updated 7 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- a deep recurrent model for exchangeable data☆34Updated 4 years ago
- python code for kernel methods☆38Updated 6 years ago
- Sparse-input neural networks☆23Updated 2 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- Code to compute the Stein discrepancy between a sample distribution and its target☆16Updated 7 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- Implicit generative models and related stuff based on the MMD, in PyTorch☆16Updated 4 years ago
- Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"☆26Updated 6 years ago
- ☆40Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 6 years ago
- ☆21Updated 6 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Code for the icml paper "zero inflated exponential family embedding"☆29Updated 7 years ago
- EigenPro2 iteration in Tensorflow (Keras)☆23Updated 6 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆33Updated 10 years ago
- FALKON implementation used in the experimental section of "FALKON: An Optimal Large Scale Kernel Method"☆30Updated 4 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 4 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated last year
- Train neural networks to use as SMC and importance sampling proposals☆24Updated 7 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Experiments of amortized stein variational gradient☆16Updated 8 years ago
- ☆12Updated last year
- Code for density estimation with nonparametric cluster shapes.☆39Updated 9 years ago