DartML / Stein-Variational-Gradient-Descent
code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
☆100Updated 6 years ago
Alternatives and similar repositories for Stein-Variational-Gradient-Descent:
Users that are interested in Stein-Variational-Gradient-Descent are comparing it to the libraries listed below
- PyTorch implementation of Stein Variational Gradient Descent☆43Updated last year
- Deep neural network kernel for Gaussian process☆202Updated 4 years ago
- ☆23Updated 3 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆83Updated 4 years ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆99Updated last year
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 6 months ago
- Random Fourier Features☆50Updated 7 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆150Updated 6 years ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆120Updated 5 years ago
- Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…☆118Updated 4 months ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆88Updated 4 years ago
- Python and MATLAB code for Stein Variational sampling methods☆25Updated 5 years ago
- The collection of recent papers about variational inference☆85Updated 5 years ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆59Updated 4 years ago
- Heterogeneous Multi-output Gaussian Processes☆52Updated 4 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆57Updated 3 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆169Updated 3 years ago
- Code for "Function Space Particle Optimization for Bayesian Neural Networks"☆17Updated 2 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 10 months ago
- Extensible Tensorflow library for differentiable particle filtering. ICML 2021.☆42Updated 2 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆58Updated 6 months ago
- Skew Gaussian Processes by Alessio Benavoli, Dario Azzimonti and Dario Piga☆14Updated 3 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆49Updated 11 months ago
- Regularized Neural ODEs (RNODE)☆82Updated 3 years ago
- Bayesian active learning with EPIG data acquisition☆31Updated last week
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆27Updated last year