BayesWatch / deep-kernel-transferLinks
Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
☆207Updated 4 years ago
Alternatives and similar repositories for deep-kernel-transfer
Users that are interested in deep-kernel-transfer are comparing it to the libraries listed below
Sorting:
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago
- Pytorch implementation of Neural Processes for functions and images☆236Updated 4 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆275Updated 3 years ago
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆117Updated 5 years ago
- Learning error bars for neural network predictions☆72Updated 6 years ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆478Updated 2 years ago
- ☆239Updated 5 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- Implementation of the variational continual learning method☆196Updated 6 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- Implementations of many meta-learning algorithms to solve the few-shot learning problem in Pytorch☆255Updated 3 years ago
- ☆252Updated 3 years ago
- ☆88Updated 4 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆114Updated 3 years ago
- Reusable BatchBALD implementation☆78Updated last year
- A brief tutorial on the Wasserstein auto-encoder☆86Updated 7 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆78Updated 2 years ago
- Code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance☆77Updated 7 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks