Learn fast, scalable, and calibrated measures of uncertainty using neural networks!
☆529Aug 31, 2021Updated 5 years ago
Alternatives and similar repositories for evidential-deep-learning
Users that are interested in evidential-deep-learning are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"☆521Jan 2, 2024Updated 2 years ago
- Implementation of Deep evidential regression paper☆58Dec 6, 2020Updated 5 years ago
- Evidential Deep Learning in PyTorch☆74Sep 27, 2022Updated 4 years ago
- Supplementary material to reproduce "The Unreasonable Effectiveness of Deep Evidential Regression"☆30Nov 28, 2022Updated 3 years ago
- Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual scree…☆136Jul 29, 2021Updated 5 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Repository for "Uncertainty Regularized Evidential Regression" published in AAAI 2024☆20Jun 30, 2024Updated 2 years ago
- Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022☆20Mar 4, 2022Updated 4 years ago
- Implementation of "Evidential Deep Learning to Quantify Classification Uncertainty" proposing a method to quantify uncertainty in a neura…☆30Sep 14, 2023Updated 3 years ago
- A curated publication list on evidential deep learning.☆192Apr 16, 2025Updated last year
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,603Oct 20, 2026Updated 2 weeks ago
- Supplementary material to reproduce "Multivariate Deep Evidential Regression"☆21Feb 25, 2022Updated 4 years ago
- Work on Evidential Deep Learning to Quantify Classification Uncertainty☆60Jan 8, 2019Updated 7 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆150Jun 2, 2023Updated 3 years ago
- Official implementation of Evidential Uncertainty Quantification: A Variance-Based Perspective [WACV 2024]☆20Sep 2, 2025Updated last year
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- Code for paper Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions.☆51Nov 3, 2023Updated 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
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆641Aug 1, 2022Updated 4 years ago
- PyTorch implementation of the original evidental-deep-learning@https://github.com/aamini/evidential-deep-learning/☆13Sep 20, 2021Updated 5 years ago
- This repository contains code for evaluating the predicted uncertainty of second-order distributions, thereby comparing a "reference" res…☆11Jul 16, 2024Updated 2 years ago
- This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning mo…☆829Oct 20, 2026Updated 2 weeks ago
- [ICML 2023] Offical implementation of the paper "Uncertainty Estimation by Fisher Information-based Evidential Deep Learning".☆47Apr 29, 2023Updated 3 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆115Jun 7, 2022Updated 4 years ago
- Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization☆2,022Mar 5, 2025Updated last year
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- Open-source framework for uncertainty and deep learning models in PyTorch 🌱☆531Sep 1, 2026Updated 2 months ago
- ☆68Dec 20, 2019Updated 6 years ago
- Code for paper "Evidence fusion with contextual discounting for multi-modality medical image segmentation"☆19Oct 9, 2022Updated 4 years ago
- Calibrating LLMs with Information-Theoretic Evidential Deep Learning (ICLR 2025)☆18Mar 2, 2025Updated last year
- Code for experiments to learn uncertainty☆31Mar 16, 2023Updated 3 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆275Mar 17, 2022Updated 4 years ago
- ☆13Feb 12, 2024Updated 2 years ago
- 【IEEE TCYB 2025】Towards Reliable Medical Image Segmentation by Modelling Evidential Calibrated Uncertainty