siboehm / NormalizingFlowNetworkLinks
Bayesian and Maximum Likelihood Implementation of the Normalizing Flow Network (NFN): https://arxiv.org/abs/1907.08982
☆21Updated 4 years ago
Alternatives and similar repositories for NormalizingFlowNetwork
Users that are interested in NormalizingFlowNetwork are comparing it to the libraries listed below
Sorting:
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated last year
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Combining smooth constraint for building DAG with normalizing flow in order to replace autoregressive transformations while keeping tract…☆45Updated last year
- 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
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- Toy Examples of Conditional Density Estimation with Bayesian Normalizing flows☆22Updated 6 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 5 years ago
- We got a stew going!☆27Updated last year
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 11 months ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆42Updated 10 months ago
- Vector Quantile Regression☆19Updated 2 months ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Recyclable Gaussian Processes☆11Updated 2 years ago
- Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'☆47Updated 3 years ago
- Implementations of normalizing flows using python and tensorflow☆24Updated 6 months ago
- simple JAX-/NumPy-based implementations of NGD with exact/approximate Fisher Information Matrix both in parameter-space and function-spac…☆14Updated 4 years ago
- Normalizing Flows using JAX☆83Updated last year
- ☆53Updated 10 months ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated 2 years ago
- ☆30Updated 2 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago