uu-sml / calibrationLinks
Python package for evaluating model calibration in classification
☆20Updated 6 years ago
Alternatives and similar repositories for calibration
Users that are interested in calibration are comparing it to the libraries listed below
Sorting:
- Non-Parametric Calibration for Classification (AISTATS 2020)☆19Updated 3 years ago
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆91Updated 5 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆51Updated 4 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆43Updated 4 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆86Updated 5 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆43Updated 2 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆112Updated 7 years ago
- Reusable BatchBALD implementation☆79Updated last year
- Python implementation of smooth optimal transport.☆61Updated 4 years ago
- ☆63Updated 5 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆90Updated last year
- ☆54Updated last year
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆93Updated 5 years ago
- ☆43Updated 7 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆151Updated 3 years ago
- A way to achieve uniform confidence far away from the training data.☆38Updated 4 years ago
- Computing various norms/measures on over-parametrized neural networks☆50Updated 7 years ago
- Source code for paper Mroueh, Sercu, Rigotti, Padhi, dos Santos, "Sobolev Independence Criterion", NeurIPS 2019☆14Updated last year
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated 2 years ago
- ☆34Updated 4 years ago
- ☆32Updated 7 years ago
- Code for Sliced Gromov-Wasserstein☆69Updated 6 years ago
- ☆251Updated 3 years ago
- Codebase for Learning Invariances in Neural Networks☆96Updated 3 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆58Updated 7 years ago
- Last-layer Laplace approximation code examples☆83Updated 4 years ago
- ☆40Updated 5 years ago
- ☆33Updated 4 years ago
- Tools for training explainable models using attribution priors.☆125Updated 4 years ago