DartML / Stein-Variational-Gradient-Descent
code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
☆99Updated 5 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☆203Updated 4 years ago
- Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)☆22Updated 5 years ago
- Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…☆118Updated 3 months ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆149Updated 6 years ago
- Random Fourier Features☆50Updated 7 years ago
- The collection of recent papers about variational inference☆85Updated 5 years ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆97Updated 11 months ago
- ☆23Updated 3 years ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆120Updated 5 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆82Updated 4 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆169Updated 3 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆27Updated last year
- Multivariate normal CDF computation for tensors. Implementation of closed form derivatives.☆12Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Pytorch implementation of Neural Processes for functions and images☆228Updated 3 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Extensible Tensorflow library for differentiable particle filtering. ICML 2021.☆41Updated 2 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated 9 months ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆58Updated 4 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- Continual Gaussian Processes☆32Updated last year
- Heterogeneous Multi-output Gaussian Processes☆52Updated 4 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 4 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- Masked Autoregressive Flow☆210Updated 8 months ago
- Code for "Function Space Particle Optimization for Bayesian Neural Networks"☆17Updated 2 years ago
- Regularized Neural ODEs (RNODE)☆82Updated 3 years ago