matthewachan / hyperdmLinks
Official repository for "Estimating Epistemic and Aleatoric Uncertainty with a Single Model"
☆22Updated 9 months ago
Alternatives and similar repositories for hyperdm
Users that are interested in hyperdm are comparing it to the libraries listed below
Sorting:
- Code for the paper "Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift"☆22Updated last year
- Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning☆194Updated this week
- Official code for "Enabling Uncertainty Estimation in Iterative Neural Networks" (ICML 2024)☆18Updated last year
- beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022☆46Updated 3 years ago
- Open-source framework for uncertainty and deep learning models in PyTorch☆424Updated this week
- ☆109Updated 4 years ago
- Simple (and cheap!) neural network uncertainty estimation☆69Updated 3 months ago
- Code for the paper "Unlocking Slot Attention by Changing Optimal Transport Costs"☆12Updated last year
- A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.☆52Updated 5 years ago
- Large-scale uncertainty benchmark in deep learning.☆62Updated 3 months ago
- 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…☆56Updated last year
- Code for "Effective Bayesian Heteroscedastic Regression with Deep Neural Networks" (NeurIPS 2023)☆21Updated 5 months ago
- Bayesian active learning with EPIG data acquisition☆34Updated 4 months ago
- [NeurIPS 2023] A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting☆212Updated 10 months ago
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆20Updated 3 years ago
- Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with…☆57Updated 2 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 5 years ago
- ☆17Updated 11 months ago
- Official implementation of Transformer Neural Processes☆78Updated 3 years ago
- Modern Fixed Point Systems using Pytorch☆103Updated last year
- Code for the paper: Rotating Features for Object Discovery☆53Updated last year
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆76Updated last year
- This repository contains an official implementation of LPBNN.☆38Updated 2 years ago
- ☆32Updated 3 years ago
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆227Updated 10 months ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆143Updated 2 years ago
- Code repository of the paper "CITRIS: Causal Identifiability from Temporal Intervened Sequences" and "iCITRIS: Causal Representation Lear…☆53Updated 2 years ago
- Neural Diffusion Processes☆81Updated last year
- Official Implementation of the paper: "A Rate-Distorion View of Uncertainty Quantification", ICML 2024☆28Updated 11 months ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆223Updated last year