ituvisionlab / EvidentialTuringProcessLinks
Evidential Calibration
☆11Updated 3 years ago
Alternatives and similar repositories for EvidentialTuringProcess
Users that are interested in EvidentialTuringProcess are comparing it to the libraries listed below
Sorting:
- Quantile risk minimization☆24Updated 10 months ago
- Supplementary material to reproduce "Multivariate Deep Evidential Regression"☆20Updated 3 years ago
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)☆28Updated 2 years ago
- Official repository for the paper "Fast Predictive Uncertainty for Classification with Bayesian Deep Networks". Accepted at UAI 2022. htt…☆12Updated 3 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Code of the paper "Beyond calibration: estimating the grouping loss of modern neural networks" published in ICLR 2023.☆12Updated last year
- ☆24Updated 3 years ago
- Pytorch implementation of the DWP with application to MRI segmentation☆9Updated 4 years ago
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".☆36Updated 3 years ago
- Early exit ensembles☆12Updated 3 years ago
- Code for the paper "Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers" published in ICLR 2019☆13Updated 6 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 3 years ago
- Code for experiments to learn uncertainty☆30Updated 2 years ago
- The official implementation of the MC-Dropconnect method for Uncertainty Estimation in DNNs☆17Updated 4 years ago
- [ICML 2021] Kernel Continual Learning☆7Updated 3 years ago
- Adaptive-binning for evaluation of confidence calibration☆12Updated 5 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆76Updated last year
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆34Updated last year
- Official code for the ICLR 2021 paper Neural ODE Processes☆72Updated 3 years ago
- Proceedings of ICML 2021☆10Updated last year
- An Empirical Framework for Domain Generalization In Clinical Settings☆30Updated 3 years ago
- An official PyTorch implementation of "Regression Prior Networks" for effective runtime uncertainty estimation.☆36Updated 4 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Dropout as Regularization and Bayesian Approximation☆58Updated 6 years ago
- PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)☆23Updated 3 years ago
- Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data (Pytorch)☆17Updated 2 years ago
- ☆32Updated 6 years ago
- Code for the paper 'Continual Learning via Sequential Function-Space Variational Inference'☆24Updated 2 years ago
- Official codebase for the paper "Provable concept learning for interpretable predictions using variational inference".☆14Updated 3 years ago
- Improving the Fairness of Chest X-ray Classifiers☆14Updated 3 years ago