aamini / evidential-deep-learningLinks
Learn fast, scalable, and calibrated measures of uncertainty using neural networks!
☆491Updated 3 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:
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆630Updated 3 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆272Updated 3 years ago
- This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"☆485Updated last year
- A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch☆614Updated 4 months ago
- ☆237Updated 5 years ago
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,524Updated 2 months ago
- Open-source framework for uncertainty and deep learning models in PyTorch☆421Updated this week
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …☆365Updated last year
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆470Updated 2 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆112Updated 3 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆143Updated 2 years ago
- ☆109Updated 4 years ago
- Laplace approximations for Deep Learning.☆515Updated 4 months ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- A simple and extensible library to create Bayesian Neural Network layers on PyTorch.☆970Updated last year
- PyTorch implementation of bayesian neural network [torchbnn]☆538Updated last year
- This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning mo…☆719Updated last month
- Reliability diagrams visualize whether a classifier model needs calibration☆155Updated 3 years ago
- An implementation of the state-of-the-art Deep Active Learning algorithms☆104Updated last year
- Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)☆205Updated 3 years ago
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆244Updated 2 years ago
- ☆469Updated 3 months ago
- This repository provides the code used to implement the framework to provide deep learning models with total uncertainty estimates as des…☆228Updated last year
- Bayesian Deep Learning Benchmarks☆672Updated 2 years ago
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆227Updated 10 months ago
- Domain adaptation made easy. Fully featured, modular, and customizable.☆381Updated 2 years ago
- 👽 Out-of-Distribution Detection with PyTorch☆308Updated 2 months ago
- Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments☆70Updated 5 years ago
- General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like a…☆45Updated 4 years ago
- Implementation of Deep evidential regression paper☆58Updated 4 years ago