google-deepmind / neural-processesLinks
This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural Processes (NPs), Attentive Neural Processes (ANPs).
☆1,005Updated 4 years ago
Alternatives and similar repositories for neural-processes
Users that are interested in neural-processes are comparing it to the libraries listed below
Sorting:
- Probabilistic Torch is library for deep generative models that extends PyTorch☆893Updated last year
- PyTorch implementations of algorithms for density estimation☆585Updated 4 years ago
- MADE (Masked Autoencoder Density Estimation) implementation in PyTorch☆585Updated 6 years ago
- Papers for Bayesian-NN☆326Updated 6 years ago
- Practical assignments of the Deep|Bayes summer school 2019☆834Updated 5 years ago
- Bayesian Deep Learning Benchmarks☆672Updated 2 years ago
- Normalizing flows in PyTorch. Current intended use is education not production.☆904Updated 5 years ago
- code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".☆663Updated 5 years ago
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆576Updated 3 years ago
- Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch☆361Updated 6 years ago
- Pytorch implementation of Augmented Neural ODEs☆551Updated 2 years ago
- Dataset to assess the disentanglement properties of unsupervised learning methods☆517Updated 4 years ago
- disentanglement_lib is an open-source library for research on learning disentangled representations.☆1,413Updated 4 years ago
- Pytorch implementation of Neural Processes for functions and images☆234Updated 3 years ago
- Bayesian neural network using Pyro and PyTorch on MNIST dataset☆315Updated 6 years ago
- Code for Implicit Generation and Generalization with Energy Based Models☆361Updated 2 years ago
- A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)☆355Updated 8 years ago
- [NeurIPS'19] Deep Equilibrium Models☆781Updated 3 years ago
- Building a Bayesian deep learning classifier☆491Updated 8 years ago
- Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation☆469Updated 6 years ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆474Updated 2 years ago
- Implementations of various VAE-based semi-supervised and generative models in PyTorch☆710Updated 5 years ago
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆634Updated 3 years ago
- higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual tr…☆1,627Updated 3 years ago
- Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)☆238Updated 7 years ago
- Code for "Latent ODEs for Irregularly-Sampled Time Series" paper☆568Updated 5 years ago
- A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.☆833Updated 4 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago
- Pytorch implementation of Hyperspherical Variational Auto-Encoders☆378Updated 5 years ago
- Pytorch implementations of density estimation algorithms: BNAF, Glow, MAF, RealNVP, planar flows☆636Updated 4 years ago