wjmaddox / swa_gaussianLinks
Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"
☆472Updated 2 years ago
Alternatives and similar repositories for swa_gaussian
Users that are interested in swa_gaussian are comparing it to the libraries listed below
Sorting:
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆272Updated 3 years ago
- ☆245Updated 2 years ago
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆632Updated 3 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆245Updated 5 years ago
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆576Updated 3 years ago
- Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)☆205Updated 3 years ago
- Laplace approximations for Deep Learning.☆517Updated 5 months ago
- ☆238Updated 5 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆151Updated 2 years ago
- Project site for "Your Classifier is Secretly an Energy-Based Model and You Should Treat it Like One"☆425Updated 3 years ago
- Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning.☆243Updated last year
- BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.☆593Updated 9 months ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆114Updated 3 years ago
- Papers for Bayesian-NN☆325Updated 6 years ago
- Bayesian Deep Learning Benchmarks☆672Updated 2 years ago
- ☆470Updated 5 months ago
- Efficient PyTorch Hessian eigendecomposition tools!☆379Updated last year
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 5 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆92Updated 4 years ago
- ☆89Updated 3 years ago
- Pytorch implementation of Neural Processes for functions and images☆233Updated 3 years ago
- A PyTorch library for two-sample tests☆242Updated 2 years ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆458Updated last year
- Reusable BatchBALD implementation☆79Updated last year
- Building a Bayesian deep learning classifier☆490Updated 7 years ago
- Learning error bars for neural network predictions☆71Updated 5 years ago
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …☆366Updated last year
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆76Updated 2 years ago