cpark321 / uncertainty-deep-learningLinks
☆238Updated 5 years ago
Alternatives and similar repositories for uncertainty-deep-learning
Users that are interested in uncertainty-deep-learning are comparing it to the libraries listed below
Sorting:
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆272Updated 3 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆632Updated 3 years ago
- Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments☆70Updated 5 years ago
- ☆109Updated 4 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
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆472Updated 2 years ago
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆576Updated 3 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆114Updated 3 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 5 years ago
- PyTorch implementation of bayesian neural network [torchbnn]☆542Updated last year
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆115Updated 4 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆57Updated 6 years ago
- Dropout as Regularization and Bayesian Approximation☆58Updated 6 years ago
- ☆40Updated 6 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆76Updated 2 years ago
- A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.☆52Updated 5 years ago
- Learning error bars for neural network predictions☆71Updated 5 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78Updated 3 years ago
- Bayesian Neural Network in PyTorch☆91Updated last year
- ☆66Updated 5 years ago
- " Weight Uncertainty in Neural Networks"☆49Updated 7 years ago
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆55Updated 2 years ago
- My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"☆139Updated 7 years ago
- Papers for Bayesian-NN☆325Updated 6 years ago
- Pytorch implementation of Neural Processes for functions and images☆233Updated 3 years ago
- ☆245Updated 2 years ago
- Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)☆137Updated 6 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆144Updated 2 years ago