A simple way to calibrate your neural network.
☆1,179Jul 26, 2025Updated last year
Alternatives and similar repositories for temperature_scaling
Users that are interested in temperature_scaling are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Calibration of Convolutional Neural Networks☆171Apr 19, 2023Updated 3 years ago
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …☆380Apr 16, 2026Updated 6 months ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆160Jan 10, 2024Updated 2 years ago
- Reliability diagrams visualize whether a classifier model needs calibration☆170Feb 11, 2022Updated 4 years ago
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,601Updated this week
- 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.
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆155Nov 10, 2022Updated 3 years ago
- NumPy library for calibration metrics☆77Apr 27, 2026Updated 5 months ago
- Local Temperature Scaling for Probability Calibration☆25Nov 26, 2021Updated 4 years ago
- On Calibration of Modern Neural Networks - tensorflow implementation☆29Jun 16, 2018Updated 8 years ago
- ☆38Nov 13, 2020Updated 5 years ago
- A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks☆234Dec 27, 2018Updated 7 years ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆477Jul 6, 2023Updated 3 years ago
- Reliability diagrams, Platt's scaling, isotonic regression☆75Aug 2, 2014Updated 12 years ago
- Code implementation of our ICLR'21 paper "Calibration of Neural Networks using Splines"☆21Mar 31, 2023Updated 3 years ago
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.☆603Jan 26, 2024Updated 2 years ago
- Adaptive-binning for evaluation of confidence calibration☆12Jul 28, 2019Updated 7 years ago
- This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"☆521Jan 2, 2024Updated 2 years ago
- AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty☆991Jul 17, 2026Updated 3 months ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆275Mar 17, 2022Updated 4 years ago
- Deep Anomaly Detection with Outlier Exposure (ICLR 2019)☆573Oct 9, 2021Updated 5 years ago
- ☆11Sep 11, 2022Updated 4 years ago
- ☆21Mar 25, 2023Updated 3 years ago
- Non-Parametric Calibration for Classification (AISTATS 2020)☆19Feb 3, 2022Updated 4 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- ☆473Oct 5, 2026Updated last week
- A simple and effective method for detecting out-of-distribution images in neural networks.☆545Oct 12, 2021Updated 5 years ago
- Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018☆182Apr 8, 2020Updated 6 years ago
- Last-layer Laplace approximation code examples☆82Oct 18, 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
- Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization☆2,019Mar 5, 2025Updated last year
- ☆441Aug 28, 2021Updated 5 years ago
- Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more☆1,976Oct 20, 2023Updated 2 years ago
- Code and datasets for the EMNLP 2020 paper "Calibration of Pre-trained Transformers"☆59Jun 12, 2023Updated 3 years ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- Principled Detection of Out-of-Distribution Examples in Neural Networks☆200Jun 28, 2017Updated 9 years ago
- Code for the paper "A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks".☆356Aug 13, 2019Updated 7 years ago
- ☆33Jun 12, 2025Updated last year
- ☆16Nov 19, 2021Updated 4 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆41Oct 20, 2023Updated 2 years ago
- Original dataset release for CIFAR-10H☆91Mar 23, 2026Updated 6 months ago
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆259Jan 23, 2023Updated 3 years ago