matthewachan / hyperdm
Official repository for "Estimating Epistemic and Aleatoric Uncertainty with a Single Model"
☆15Updated 5 months ago
Alternatives and similar repositories for hyperdm:
Users that are interested in hyperdm are comparing it to the libraries listed below
- Large-scale uncertainty benchmark in deep learning.☆56Updated 2 months ago
- Simple (and cheap!) neural network uncertainty estimation☆63Updated 2 weeks ago
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆21Updated 2 years ago
- ☆32Updated 2 years ago
- Official code for "Enabling Uncertainty Estimation in Iterative Neural Networks" (ICML 2024)☆16Updated 9 months ago
- Code for the paper "Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift"☆22Updated last year
- Bayesian active learning with EPIG data acquisition☆31Updated this week
- Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with…☆55Updated 2 years ago
- Code for "Effective Bayesian Heteroscedastic Regression with Deep Neural Networks" (NeurIPS 2023)☆20Updated last month
- beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022☆43Updated 3 years ago
- Instructions and examples to deploy some PyTorch code on slurm using a Singularity Container☆33Updated 2 years ago
- Example code of Sparse Gaussian Process Attention (ICLR 2023)☆24Updated 9 months ago
- Code for the paper: Complex-Valued Autoencoders for Object Discovery☆50Updated 2 years ago
- ☆104Updated 3 years ago
- ☆25Updated last year
- A meta repository pointing to the other repositories where the implementation of the supplementary examples for our tutorial "Hands-on Ba…☆127Updated 3 years ago
- Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning☆175Updated this week
- A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…☆52Updated last year
- Official code for the ICLR 2021 paper Neural ODE Processes☆72Updated 2 years ago
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆17Updated 2 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆88Updated 4 years ago
- Official Implementation of the paper: "A Rate-Distorion View of Uncertainty Quantification", ICML 2024☆28Updated 7 months ago
- A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.☆50Updated 5 years ago
- ☆17Updated 7 months ago
- Official implementation of Transformer Neural Processes☆74Updated 2 years ago
- Algorithms for computations on random manifolds made easier☆90Updated last year
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆75Updated last year
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago
- On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification☆21Updated 3 years ago
- Conformal prediction for uncertainty quantification in image segmentation☆22Updated 4 months ago