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:
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)☆28Updated 2 years ago
- ☆25Updated 3 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
- Uncertainty Aware Semi-Supervised Learning on Graph Data☆38Updated 4 years ago
- Quantile risk minimization☆24Updated last year
- Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data (Pytorch)☆17Updated 3 years ago
- An official PyTorch implementation of "Regression Prior Networks" for effective runtime uncertainty estimation.☆36Updated 4 years ago
- The official implementation of the MC-Dropconnect method for Uncertainty Estimation in DNNs☆17Updated 5 years ago
- ☆13Updated 5 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78Updated 3 years ago
- Proceedings of ICML 2021☆10Updated last month
- Implementation of the paper "Understanding anomaly detection with deep invertible networks through hierarchies of distributions and featu…☆42Updated 4 years ago
- ☆51Updated 4 years ago
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".☆36Updated 3 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 3 years ago
- A Pytorch implementation of missing data imputation using optimal transport.☆103Updated 4 years ago
- [NeurIPS 2020]. COPT - Coordinated Optimal Transport on Graphs☆16Updated 4 years ago
- Code for our MIDL2020 submission "Well-Calibrated Regression Uncertainty in Medical Imaging with Deep Learning".☆31Updated 4 years ago
- Official codebase for the paper "Provable concept learning for interpretable predictions using variational inference".☆14Updated 3 years ago
- Work on Evidential Deep Learning to Quantify Classification Uncertainty☆60Updated 6 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆36Updated last year
- Signal compression and reconstruction on complexes preserving topological features via Discrete Morse Theory☆14Updated 3 years ago
- Supplementary material to reproduce "Multivariate Deep Evidential Regression"☆20Updated 3 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆57Updated 6 years ago
- PyTorch implementation of SNGP as found in https://arxiv.org/pdf/2006.10108.pdf☆16Updated last year
- ☆14Updated 2 years ago
- Code for experiments to learn uncertainty☆30Updated 2 years ago
- ☆38Updated 4 years ago
- Last-layer Laplace approximation code examples☆84Updated 3 years ago