This repository contains recent research on uncertainty estimation. Inspired from other 'awesome' github pages like awesome-deep-learning.
- [ICLR'20] PITFALLS OF IN-DOMAIN UNCERTAINTY ESTIMATION AND ENSEMBLING IN DEEP LEARNING link
- [ICML'20] Can Your AI Differentiate Cats from Covid-19? Sample Efficient Uncertainty Estimation for Deep Learning Safety [link]
- [NIPS'19] Can You Trust Your Model’s Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift link
- [NIPS'19] Single-Model Uncertainties for Deep Learning link
- [ICML'19] Uncertainty Estimation Using a Single Deep Deterministic Neural Network link code
- [NIPS'17] Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles link
- [ICML'16] Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning link
- [ACL'20] Estimating predictive uncertainty for rumour verification models linkcode
- [AAAI'19] Quantifying Uncertainties in Natural Language Processing Tasks link
- (2020) Uncertainty Estimation Using a Single Deep Deterministic Neural Network link
- (2020) Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness link
- (2019) Exploring Uncertainty Measures for Image-Caption Embedding-and-Retrieval Task link
- [ICML'20] https://sites.google.com/view/udlworkshop2020/home
- [ICML'19] https://sites.google.com/view/udlworkshop2019/home
There are many more papers to be added. Please feel free to make pull-resquest to add more papers, especially foundational papers.