Code for experiments to learn uncertainty
☆31Mar 16, 2023Updated 3 years ago
Alternatives and similar repositories for DEUP
Users that are interested in DEUP are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Official repository for the paper "Fast Predictive Uncertainty for Classification with Bayesian Deep Networks". Accepted at UAI 2022. htt…☆13May 25, 2022Updated 4 years ago
- Companion code for the paper "Learnable Uncertainty under Laplace Approximations" (UAI 2021).☆19Jun 8, 2021Updated 5 years ago
- Code for "Training, Architecture, and Prior for Deterministic Uncertainty Methods" ICLR 2023 Workshop on Trustworthy ML☆12Jun 15, 2023Updated 3 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆150Jun 2, 2023Updated 3 years ago
- Supplementary material to reproduce "Multivariate Deep Evidential Regression"☆21Feb 25, 2022Updated 4 years ago
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)☆28Nov 28, 2022Updated 3 years ago
- This repository contains an official implementation of LPBNN.☆38Jun 28, 2023Updated 3 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78May 18, 2022Updated 4 years ago
- ☆10Sep 14, 2022Updated 3 years ago
- Official implementation of "How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts?", TMLR 2023.☆19Mar 21, 2024Updated 2 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆275Mar 17, 2022Updated 4 years ago
- Official code for "ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference" (TMLR 2024)☆17Nov 7, 2024Updated last year
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆115Jun 7, 2022Updated 4 years ago
- Code and models for our paper "Risk-Aware Machine Learning Classifier for Skin Lesion Diagnosis"☆10Aug 2, 2024Updated last year
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- Official Code: Estimating Model Uncertainty of Neural Networks in Sparse Information Form, ICML2020.☆31Mar 3, 2021Updated 5 years ago
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆641Aug 1, 2022Updated 3 years ago
- My implementation of https://arxiv.org/abs/1910.02600 in pytorch. Based on https://github.com/aamini/evidential-deep-learning☆10Jan 26, 2021Updated 5 years ago
- ☆18Sep 3, 2024Updated last year
- Fast, Simple and Easy to use SOTA Self-Supervised Image Classification Models in PyTorch☆17Aug 18, 2021Updated 4 years ago
- ☆15May 20, 2026Updated 2 months ago
- Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')☆17Oct 12, 2022Updated 3 years ago
- Every Call is Precious: Global Optimization of Black-Box Functions with Unknown Lipschitz Constants☆16Apr 23, 2026Updated 3 months ago
- The official source code to: Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition (AISTATS'23)☆11Apr 21, 2023Updated 3 years ago
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- [ICLR 2026] Official code for BézierFlow: Learning Bézier Stochastic Interpolant Schedulers for Few-Step Generation☆21Apr 13, 2026Updated 3 months ago
- Quantification of Uncertainty with Adversarial Models☆29Jul 11, 2023Updated 3 years ago
- Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)☆44Nov 25, 2024Updated last year
- [CVPRW 2024] Conformal prediction for uncertainty quantification in image segmentation☆27Dec 9, 2024Updated last year
- Automatic Integration for Neural Spatio-Temporal Point Process models (AI-STPP) is a new paradigm for exact, efficient, non-parametric inf…☆25Oct 14, 2024Updated last year
- A library for uncertainty quantification based on PyTorch☆119Jan 10, 2022Updated 4 years ago
- Official implementation of Evidential Uncertainty Quantification: A Variance-Based Perspective [WACV 2024]☆19Sep 2, 2025Updated 10 months ago
- ☆24Dec 10, 2022Updated 3 years ago
- ☆110Jun 29, 2021Updated 5 years ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- Supplementary material to reproduce "The Unreasonable Effectiveness of Deep Evidential Regression"☆30Nov 28, 2022Updated 3 years ago
- ☆11Apr 18, 2021Updated 5 years ago
- PyTorch implementation of Probabilistic MIMO U-Net☆22Aug 15, 2024Updated last year
- ☆15Jul 18, 2019Updated 7 years ago
- [ICML 2023] Offical implementation of the paper "Uncertainty Estimation by Fisher Information-based Evidential Deep Learning".☆44Apr 29, 2023Updated 3 years ago
- Code related to different aspects of conformal learning☆18Jan 28, 2025Updated last year
- Belief matching framework official implementation☆41Mar 24, 2023Updated 3 years ago