alartum / sngp-pytorchLinks
Spectral-normalized Neural Gaussian Process (SNGP) implementation in PyTorch
☆9Updated 3 years ago
Alternatives and similar repositories for sngp-pytorch
Users that are interested in sngp-pytorch are comparing it to the libraries listed below
Sorting:
- Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments☆69Updated 5 years ago
- My implementation of https://arxiv.org/abs/1910.02600 in pytorch. Based on https://github.com/aamini/evidential-deep-learning☆10Updated 4 years ago
- Code for the paper 'Continual Learning via Sequential Function-Space Variational Inference'☆24Updated 2 years ago
- ☆108Updated 3 years ago
- A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.☆51Updated 5 years ago
- A hello world Bayesian Neural Network project on MNIST☆44Updated 3 years ago
- A meta repository pointing to the other repositories where the implementation of the supplementary examples for our tutorial "Hands-on Ba…☆130Updated 3 years ago
- Code for "Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference" (NeurIPS Bayesian Deep Learning W…☆24Updated 5 years ago
- Repository for 'Interpretable embeddings from molecular simulations using gaussian mixture variational autoencoders'☆20Updated 5 years ago
- Implementation of deep kernels in GPyTorch and Pyro☆10Updated 4 years ago
- The official implementation of the MC-Dropconnect method for Uncertainty Estimation in DNNs☆17Updated 4 years ago
- Regression datasets from the UCI repository with standardized test-train splits.☆47Updated 2 years ago
- Dropout as Regularization and Bayesian Approximation☆58Updated 6 years ago
- ☆39Updated 6 years ago
- A toy example of VAE-regression network☆72Updated 5 years ago
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆16Updated 2 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆56Updated 6 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 2 years ago
- ☆152Updated 2 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆112Updated 3 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆77Updated 3 years ago
- " Weight Uncertainty in Neural Networks"☆49Updated 7 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 3 years ago
- ☆10Updated last year
- Various code/notebooks to benchmark different ways we could estimate uncertainty in ML predictions.☆42Updated 4 years ago
- Code repository for review paper titled "Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A …☆27Updated last year
- This repo contains a PyTorch implementation of the paper: "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles"☆13Updated 3 years ago
- PyTorch implementation of 'Concrete Dropout'☆15Updated last year
- Example code of Sparse Gaussian Process Attention (ICLR 2023)☆24Updated 11 months ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago