aamini / evidential-deep-learning
Learn fast, scalable, and calibrated measures of uncertainty using neural networks!
☆455Updated 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
- This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"☆453Updated last year
- Open-source framework for uncertainty and deep learning models in PyTorch☆348Updated 2 weeks ago
- Laplace approximations for Deep Learning.☆495Updated last week
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,480Updated last week
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆271Updated 2 years ago
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆617Updated 2 years ago
- ☆229Updated 4 years ago
- A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch☆563Updated 2 weeks ago
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …☆353Updated 6 months ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆456Updated last year
- Reliability diagrams visualize whether a classifier model needs calibration☆145Updated 3 years ago
- ☆468Updated 6 months ago
- This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning mo…☆622Updated 2 months ago
- ☆300Updated 2 months ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆110Updated 2 years ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆159Updated last year
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆152Updated 2 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆131Updated last year
- PyTorch implementation of bayesian neural network [torchbnn]☆509Updated 6 months ago
- This repository provides the code used to implement the framework to provide deep learning models with total uncertainty estimates as des…☆227Updated 6 months ago
- Bayesian Deep Learning Benchmarks☆667Updated last year
- Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020☆235Updated 2 years ago
- Domain adaptation made easy. Fully featured, modular, and customizable.☆365Updated 2 years ago
- ☆99Updated 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…☆235Updated 2 years ago
- ☆236Updated 2 years ago
- A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.☆558Updated last year
- Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)☆202Updated 3 years ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆431Updated 5 months ago
- Cockpit: A Practical Debugging Tool for Training Deep Neural Networks☆474Updated 2 years ago