Tom271 / LangevinMC
MIGSAA Project 2 - Langevin Monte Carlo Algorithms
☆12Updated last year
Alternatives and similar repositories for LangevinMC:
Users that are interested in LangevinMC are comparing it to the libraries listed below
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Gaussian Processes for Sequential Data☆18Updated 4 years ago
- Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models☆19Updated 2 years ago
- Python and MATLAB code for Stein Variational sampling methods☆25Updated 5 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- ☆28Updated 6 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆82Updated 4 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- Library for Deep Gaussian Processes based on GPflow☆19Updated 4 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 2 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Variational Gaussian Process State-Space Models☆23Updated 9 years ago
- Continual Gaussian Processes☆32Updated last year
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆27Updated last year
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- ☆23Updated 3 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆31Updated 3 years ago
- ☆15Updated 2 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆41Updated 8 months ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Code accompanying the paper "Probabilistic Selection of Inducing Points in Sparse Gaussian Processes".☆24Updated 2 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated 9 months ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 6 years ago
- Methods and experiments for assumed density SDE approximations☆11Updated 3 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆71Updated 4 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆46Updated last year