federicobergamin / Variational-Inference-with-Normalizing-FlowsLinks
Personal implementation of "Variational Inference with Normalizing Flows" by [Rezende, et al., 2015] in PyTorch
☆23Updated 6 years ago
Alternatives and similar repositories for Variational-Inference-with-Normalizing-Flows
Users that are interested in Variational-Inference-with-Normalizing-Flows are comparing it to the libraries listed below
Sorting:
- Code required to reproduce the experiments in Auxiliary Variational MCMC☆17Updated 7 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 6 years ago
- A Pytorch Implementation of Attentive Neural Process☆75Updated 6 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- ☆149Updated 3 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆36Updated 4 years ago
- Pytorch implementation of Neural Processes for functions and images☆236Updated 3 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
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆57Updated last year
- Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)☆85Updated 3 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Featurized Density Ratio Estimation☆20Updated 4 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- ☆54Updated last year
- Sample code for running deterministic variational inference to train Bayesian neural networks☆102Updated 7 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 5 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆86Updated 5 years ago
- Implementation of the Convolutional Conditional Neural Process☆128Updated 4 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆78Updated 2 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆47Updated 5 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆76Updated 3 years ago
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆63Updated 5 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆34Updated 4 years ago
- ODE2VAE: Deep generative second order ODEs with Bayesian neural networks☆131Updated last year
- Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)☆244Updated 7 years ago
- Monotone operator equilibrium networks☆54Updated 5 years ago
- Ladder Variational Autoencoders (LVAE) in PyTorch☆92Updated 5 years ago
- Variational auto encoder in pytorch☆56Updated 6 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- The collection of recent papers about variational inference☆84Updated 6 years ago