google-deepmind / neural-processes
This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural Processes (NPs), Attentive Neural Processes (ANPs).
☆988Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for neural-processes
- Probabilistic Torch is library for deep generative models that extends PyTorch☆887Updated 6 months ago
- Pytorch implementation of Neural Processes for functions and images☆225Updated 2 years ago
- PyTorch implementations of algorithms for density estimation☆577Updated 3 years ago
- Bayesian Deep Learning Benchmarks☆663Updated last year
- code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".☆629Updated 4 years ago
- disentanglement_lib is an open-source library for research on learning disentangled representations.☆1,388Updated 3 years ago
- Papers for Bayesian-NN☆314Updated 5 years ago
- Pytorch implementation of Augmented Neural ODEs☆532Updated last year
- Normalizing flows in PyTorch. Current intended use is education not production.☆846Updated 4 years ago
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆555Updated 2 years ago
- A highly efficient implementation of Gaussian Processes in PyTorch☆3,582Updated this week
- Neural relational inference for interacting systems - pytorch☆741Updated 5 years ago
- Practical assignments of the Deep|Bayes summer school 2019☆827Updated 4 years ago
- Dataset to assess the disentanglement properties of unsupervised learning methods☆483Updated 3 years ago
- higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual tr…☆1,593Updated 2 years ago
- MADE (Masked Autoencoder Density Estimation) implementation in PyTorch☆539Updated 5 years ago
- Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch☆359Updated 5 years ago
- [NeurIPS'19] Deep Equilibrium Models☆727Updated 2 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆242Updated 4 years ago
- Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations☆692Updated 8 months ago
- Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation☆461Updated 5 years ago
- Fast and Easy Infinite Neural Networks in Python☆2,279Updated 8 months ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆454Updated last year
- Bayesian neural network using Pyro and PyTorch on MNIST dataset☆308Updated 5 years ago
- Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more☆1,844Updated last year
- A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.☆787Updated 3 years ago
- Implementations of various VAE-based semi-supervised and generative models in PyTorch☆707Updated 4 years ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆203Updated 5 months ago
- Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)☆228Updated 6 years ago
- A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)☆336Updated 7 years ago