rahulrahaman / Uncertainty-Quantification-and-Deep-EnsembleLinks
Experiments from our work Uncertainty Quantification and Deep Ensemble
☆10Updated 4 years ago
Alternatives and similar repositories for Uncertainty-Quantification-and-Deep-Ensemble
Users that are interested in Uncertainty-Quantification-and-Deep-Ensemble are comparing it to the libraries listed below
Sorting:
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- ☆38Updated 5 years ago
- General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like a…☆45Updated 5 years ago
- Last-layer Laplace approximation code examples☆83Updated 4 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Bayesianize: A Bayesian neural network wrapper in pytorch☆92Updated last year
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 5 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- Learning error bars for neural network predictions☆72Updated 6 years ago
- Dropout as Regularization and Bayesian Approximation☆58Updated 7 years ago
- Welcome to Uncertainty Metrics! The goal of this library is to provide an easy-to-use interface for both measuring uncertainty across Goo…☆24Updated 5 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆58Updated 7 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆114Updated 3 years ago
- ☆25Updated 3 years ago
- Explores the ideas presented in Deep Ensembles: A Loss Landscape Perspective (https://arxiv.org/abs/1912.02757) by Stanislav Fort, Huiyi …☆66Updated 5 years ago
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆117Updated 5 years ago
- Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …☆41Updated 5 years ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆161Updated 2 years ago
- Code for the paper "Rethinking Importance Weighting for Deep Learning under Distribution Shift".☆30Updated 4 years ago
- PyTorch implementation of FIM and empirical FIM☆60Updated 7 years ago
- Reusable BatchBALD implementation☆78Updated last year
- Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')☆17Updated 3 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated 2 years ago
- Active and Sample-Efficient Model Evaluation☆26Updated 8 months ago
- " Weight Uncertainty in Neural Networks"☆49Updated 8 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆39Updated 3 years ago
- Path-SGD: Path-Normalized Optimization in Deep Neural Networks☆19Updated 7 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆275Updated 3 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆60Updated 4 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆86Updated 5 years ago