Tom271 / LangevinMCLinks
MIGSAA Project 2 - Langevin Monte Carlo Algorithms
☆15Updated last year
Alternatives and similar repositories for LangevinMC
Users that are interested in LangevinMC are comparing it to the libraries listed below
Sorting:
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Gaussian Processes for Sequential Data☆18Updated 4 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 2 years ago
- ☆24Updated 3 years ago
- Toy Examples of Conditional Density Estimation with Bayesian Normalizing flows☆22Updated 6 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 4 years ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆103Updated last year
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆104Updated last year
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- Masked Autoregressive Flow☆213Updated 11 months ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆42Updated 11 months ago
- We got a stew going!☆27Updated last year
- Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…☆120Updated 6 months ago
- Sliced Iterative Generator (SIG) & Gaussianizing Iterative Slicing (GIS)☆37Updated 2 years ago
- Implementation of the Gaussian Process Autoregressive Regression Model☆67Updated 5 months ago
- ☆28Updated 6 years ago
- Conditional density estimation with neural networks☆31Updated 5 months ago
- Methods and experiments for assumed density SDE approximations☆12Updated 3 years ago
- Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models☆20Updated 3 years ago
- Implementations of Normalizing Flows in Pytorch/Pyro☆19Updated 5 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 2 years ago
- Package implementing various parametric and nonparametric methods for conditional density estimation☆197Updated 2 years ago
- Code accompanying the paper "Probabilistic Selection of Inducing Points in Sparse Gaussian Processes".☆25Updated 2 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Sequential Neural Likelihood☆40Updated 5 years ago