geniki / neural-processes
PyTorch implementation of Neural Processes
☆88Updated 5 years ago
Alternatives and similar repositories for neural-processes:
Users that are interested in neural-processes are comparing it to the libraries listed below
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Pytorch implementation of Neural Processes for functions and images☆228Updated 2 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆80Updated 4 years ago
- The collection of recent papers about variational inference☆85Updated 5 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆32Updated last year
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 4 years ago
- A Pytorch Implementation of Attentive Neural Process☆72Updated 5 years ago
- Understanding normalizing flows☆131Updated 5 years ago
- simple implementation of "Improved Variational Inference with Inverse Autoregressive Flow" paper with pytorch☆53Updated 7 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆110Updated 6 years ago
- Variational Autoencoder for Unsupervised and Disentangled Representation Learning of content and motion features in sequential data (Mand…☆104Updated 5 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆53Updated 3 months ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 5 years ago
- Code for the paper "VAE with a VampPrior", J.M. Tomczak & M. Welling☆224Updated 6 years ago
- PyTorch Implementations of Dropout Variants☆87Updated 7 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆101Updated 6 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆48Updated 6 years ago
- Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"☆99Updated 8 years ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆119Updated 5 years ago
- PyTorch Implementation of Neural Statistician☆60Updated 2 years ago
- Experiments for the Neural Autoregressive Flows paper☆124Updated 3 years ago
- Gaussian Process Prior Variational Autoencoder☆81Updated 6 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆50Updated 7 years ago
- a python implementation of various versions of the information bottleneck, including automated parameter searching☆122Updated 4 years ago
- Pytorch Adversarial Auto Encoder (AAE)☆86Updated 5 years ago
- Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019☆39Updated 4 years ago
- Optimizing control variates for black-box gradient estimation☆162Updated 5 years ago
- Deep convolutional gaussian processes.☆78Updated 5 years ago