EFS-OpenSource / calibration-framework
The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a neural network.
☆347Updated 3 months ago
Related projects ⓘ
Alternatives and complementary repositories for calibration-framework
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆143Updated 2 years ago
- Open-source framework for uncertainty and deep learning models in PyTorch☆305Updated this week
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆268Updated 2 years ago
- Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020☆235Updated last year
- Calibration of Convolutional Neural Networks☆158Updated last year
- ☆466Updated 3 months ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆155Updated 10 months ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆454Updated last year
- A simple way to calibrate your neural network.☆1,104Updated 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…☆229Updated last year
- Reliability diagrams visualize whether a classifier model needs calibration☆137Updated 2 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆111Updated 2 years ago
- Laplace approximations for Deep Learning.☆471Updated this week
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆129Updated last year
- A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.☆551Updated 9 months ago
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,452Updated last month
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆611Updated 2 years ago
- This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"☆438Updated 10 months ago
- ☆400Updated 3 years ago
- DISTIL: Deep dIverSified inTeractIve Learning. An active/inter-active learning library built on py-torch for reducing labeling costs.☆142Updated last year
- Reusable BatchBALD implementation☆74Updated 8 months ago
- Bayesian active learning library for research and industrial usecases.☆869Updated 4 months ago
- CORAL and CORN implementations for ordinal regression with deep neural networks.☆225Updated last year
- This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning mo…☆576Updated last month
- Implementation of Estimating Training Data Influence by Tracing Gradient Descent (NeurIPS 2020)☆219Updated 2 years ago
- An implementation of the BADGE batch active learning algorithm.☆197Updated 5 months ago
- ☆235Updated last year
- Optimal Transport Dataset Distance☆156Updated 2 years ago
- 👽 Out-of-Distribution Detection with PyTorch☆252Updated last week