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:
- Variational Fourier Features☆86Updated 4 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- Implementation of linear CorEx and temporal CorEx.☆37Updated 3 years ago
- ☆40Updated 6 years ago
- a deep recurrent model for exchangeable data☆34Updated 5 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆33Updated 10 years ago
- NeurIPS 2018. Linear-time model comparison tests.☆18Updated 5 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- State space modeling with recurrent neural networks☆45Updated 7 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- Code for density estimation with nonparametric cluster shapes.☆39Updated 9 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Hierarchical Change-Point Detection☆14Updated 6 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Foundations and Applications☆98Updated 5 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- ☆51Updated 11 months ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆39Updated 8 years ago
- A distributed method for fitting Laplacian regularized stratified models.☆25Updated 4 years ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆23Updated 6 years ago
- ☆12Updated 7 years ago
- Neural Processes implementation for 1D regression☆65Updated 6 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- ☆28Updated 6 years ago
- Pytorch implementation of Recurrent Neural Processes https://arxiv.org/pdf/1906.05915.pdf☆22Updated 5 years ago
- Code for "Deep Signature Transforms" (NeurIPS 2019)☆94Updated 11 months ago