aamini / evidential-deep-learningLinks
Learn fast, scalable, and calibrated measures of uncertainty using neural networks!
☆498Updated 4 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
Sorting:
- This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"☆499Updated last year
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆272Updated 3 years ago
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆631Updated 3 years ago
- ☆239Updated 5 years ago
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,545Updated last week
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆145Updated 2 years ago
- A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch☆633Updated 6 months ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆473Updated 2 years ago
- Open-source framework for uncertainty and deep learning models in PyTorch☆442Updated 3 weeks ago
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …☆368Updated last year
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆114Updated 3 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- Laplace approximations for Deep Learning.☆523Updated 6 months ago
- Reliability diagrams visualize whether a classifier model needs calibration☆160Updated 3 years ago
- ☆109Updated 4 years ago
- An implementation of the state-of-the-art Deep Active Learning algorithms☆105Updated 2 years ago
- PyTorch implementation of bayesian neural network [torchbnn]☆550Updated last year
- This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning mo…☆756Updated 2 months ago
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆251Updated 2 years ago
- 👽 Out-of-Distribution Detection with PyTorch☆328Updated last month
- A simple and extensible library to create Bayesian Neural Network layers on PyTorch.☆979Updated 2 years ago
- Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)☆206Updated 3 years ago
- A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.☆581Updated last year
- This repository provides the code used to implement the framework to provide deep learning models with total uncertainty estimates as des…☆229Updated last year
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆239Updated last year
- Domain adaptation made easy. Fully featured, modular, and customizable.☆387Updated 2 years ago
- ☆250Updated 2 years ago
- ☆471Updated last month
- Implementation of Deep evidential regression paper☆57Updated 4 years ago
- ☆426Updated 4 years ago