mariushobbhahn / LB_for_BNNs_officialLinks
Official repository for the paper "Fast Predictive Uncertainty for Classification with Bayesian Deep Networks". Accepted at UAI 2022. https://arxiv.org/abs/2003.01227
☆12Updated 3 years ago
Alternatives and similar repositories for LB_for_BNNs_official
Users that are interested in LB_for_BNNs_official are comparing it to the libraries listed below
Sorting:
- Code for experiments to learn uncertainty☆30Updated 2 years ago
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)☆28Updated 3 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78Updated 3 years ago
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".☆37Updated 3 years ago
- This repository contains an official implementation of LPBNN.☆38Updated 2 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- ☆13Updated 5 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 4 years ago
- Code for the ICML 2021 and ICLR 2022 papers: Skew Orthogonal Convolutions, Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100☆18Updated 3 years ago
- Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)☆44Updated last year
- ☆42Updated 6 years ago
- Code for the paper "Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers" published in ICLR 2019☆14Updated 6 years ago
- An official PyTorch implementation of "Regression Prior Networks" for effective runtime uncertainty estimation.☆36Updated 5 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆35Updated last year
- C-Mixup for NeurIPS 2022☆73Updated 2 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆78Updated 2 years ago
- Quantile risk minimization☆25Updated last year
- Official Code: Estimating Model Uncertainty of Neural Networks in Sparse Information Form, ICML2020.☆31Updated 4 years ago
- Repository for the NeurIPS 2023 paper "Beyond Confidence: Reliable Models Should Also Consider Atypicality"☆13Updated last year
- Code repository for the AISTATS 2021 paper "Towards Understanding the Optimal Behaviors of Deep Active Learning Algorithms"☆15Updated 4 years ago
- ☆41Updated 5 years ago
- Last-layer Laplace approximation code examples☆83Updated 4 years ago
- Harvard Fall 2019 Applied Math 207 A Primer and Critique of Prior Networks☆12Updated 6 years ago
- Hyperbolic Busemann Learning with Ideal Prototypes, NeurIPS2021☆24Updated 4 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆36Updated 4 years ago
- Official PyTorch implementation of "Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error"☆37Updated 2 years ago
- Experiments on meta-learning algorithms to solve few-shot domain adaptation☆10Updated 4 years ago
- ☆53Updated 7 years ago
- Energy Based Models are a quite novel technique for density estimation. In this university project I explore this new research topic and …☆16Updated 4 years ago
- Learning Representations that Support Robust Transfer of Predictors☆20Updated 4 years ago