karlnapf / ds3_kernel_testingLinks
Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"
☆26Updated 6 years ago
Alternatives and similar repositories for ds3_kernel_testing
Users that are interested in ds3_kernel_testing are comparing it to the libraries listed below
Sorting:
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- NeurIPS 2018. Linear-time model comparison tests.☆18Updated 5 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Implementation of linear CorEx and temporal CorEx.☆37Updated 3 years ago
- Hierarchical Change-Point Detection☆14Updated 6 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- ☆40Updated 6 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- Variational Fourier Features☆85Updated 3 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆33Updated 10 years ago
- Code for density estimation with nonparametric cluster shapes.☆39Updated 8 years ago
- a deep recurrent model for exchangeable data☆34Updated 4 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆47Updated 2 years ago
- Implicit generative models and related stuff based on the MMD, in PyTorch☆16Updated 4 years ago
- State space modeling with recurrent neural networks☆45Updated 7 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 5 years ago
- Code required to reproduce the experiments in Auxiliary Variational MCMC☆17Updated 6 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Scaled MMD GAN☆36Updated 5 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆32Updated 4 years ago
- Source for experiments in the Additive Gaussian process paper, as well as extensions relating to dropout.☆22Updated 11 years ago
- A distributed method for fitting Laplacian regularized stratified models.☆25Updated 4 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆39Updated 8 years ago
- Code for Randomly Projected Additive Gaussian Processes☆25Updated 5 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 11 months ago
- Reweighted Expectation Maximization☆29Updated 5 years ago
- ☆12Updated 7 years ago