Tom271 / LangevinMCLinks
MIGSAA Project 2 - Langevin Monte Carlo Algorithms
☆15Updated 2 years ago
Alternatives and similar repositories for LangevinMC
Users that are interested in LangevinMC are comparing it to the libraries listed below
Sorting:
- Sequential Neural Likelihood☆42Updated 6 years ago
- A community repository for benchmarking Bayesian methods☆112Updated 4 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆86Updated 5 years ago
- Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…☆125Updated 2 weeks ago
- ☆24Updated 4 years ago
- Manifold Markov chain Monte Carlo methods in Python☆237Updated last week
- Heterogeneous Multi-output Gaussian Processes☆54Updated 5 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆100Updated 6 years ago
- Masked Autoregressive Flow☆218Updated last year
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆108Updated last year
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- ☆155Updated 3 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Code accompanying the paper "Probabilistic Selection of Inducing Points in Sparse Gaussian Processes".☆25Updated 3 years ago
- The collection of recent papers about variational inference☆84Updated 6 years ago
- Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models☆20Updated 3 years ago
- Manifold-learning flows (ℳ-flows)☆231Updated 5 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆25Updated last year
- Code for Neural Spline Flows paper☆283Updated 2 months ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Package implementing various parametric and nonparametric methods for conditional density estimation☆197Updated this week
- Example codes for the book Applied Stochastic Differential Equations☆202Updated last month
- PyTorch implementation of the Masked Autoregressive Flow☆30Updated 4 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated last year
- Implementation of normalizing flows in TensorFlow 2 including a small tutorial.☆146Updated 2 months ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- Toy Examples of Conditional Density Estimation with Bayesian Normalizing flows☆20Updated 7 years ago
- Gaussian Processes for Sequential Data☆19Updated 5 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago