OxfordML / bayesquadLinks
Library for Bayesian Quadrature
☆32Updated 6 years ago
Alternatives and similar repositories for bayesquad
Users that are interested in bayesquad are comparing it to the libraries listed below
Sorting:
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 6 months ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Nonparametric Differential Equation Modeling☆54Updated last year
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- ☆38Updated 5 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆20Updated 3 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Extensible Tensorflow library for differentiable particle filtering. ICML 2021.☆42Updated 2 years ago
- Combining smooth constraint for building DAG with normalizing flow in order to replace autoregressive transformations while keeping tract…☆45Updated last year
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆74Updated 3 years ago
- Modular Gaussian Processes☆15Updated 3 years ago
- ☆15Updated 2 years ago
- Implementations of Normalizing Flows in Pytorch/Pyro☆19Updated 5 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- ☆52Updated 2 years ago
- Kernel Identification Through Transformers☆13Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 5 years ago
- Re-implementation of Hamiltonian Generative Networks paper☆33Updated 3 years ago
- Lightweight MCMC sampling for PyTorch Models aka My Corona Project☆49Updated 2 weeks ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- Refining continuous-in-depth neural networks☆42Updated 3 years ago
- [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)☆22Updated 4 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆34Updated 3 years ago