JeremyNixon / uncertainty-metrics-1Links
An easy-to-use interface for measuring uncertainty and robustness.
☆15Updated 4 years ago
Alternatives and similar repositories for uncertainty-metrics-1
Users that are interested in uncertainty-metrics-1 are comparing it to the libraries listed below
Sorting:
- Reusable BatchBALD implementation☆78Updated last year
- This is reimplementation of "Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness" in Pyt…☆52Updated 4 years ago
- Reliability diagrams visualize whether a classifier model needs calibration☆164Updated 3 years ago
- Deep Batch Active Learning for Regression☆71Updated last year
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆114Updated 3 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆43Updated 7 months ago
- Deep Bayesian Active Learning with Image Data by Gal et al. (ICML 2017)☆46Updated 3 years ago
- Human-AI Deferral Evaluation Benchmark (Learning to Defer) AISTATS23☆22Updated 2 years ago
- NumPy library for calibration metrics☆73Updated 3 months ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆161Updated last year
- Welcome to Uncertainty Metrics! The goal of this library is to provide an easy-to-use interface for both measuring uncertainty across Goo…☆24Updated 5 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆275Updated 3 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆145Updated 2 years ago
- ☆10Updated 2 years ago
- Code implementation of our ICLR'21 paper "Calibration of Neural Networks using Splines"☆22Updated 2 years ago
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆255Updated 2 years ago
- Pacmed Labs experiments on uncertainty estimation, focusing on unbalanced tabular data and classification tasks.☆21Updated 4 years ago
- Implementation of "Evidential Deep Learning to Quantify Classification Uncertainty" proposing a method to quantify uncertainty in a neura…☆30Updated 2 years ago
- ☆111Updated 3 years ago
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆73Updated last year
- Framework code with wandb, checkpointing, logging, configs, experimental protocols. Useful for fine-tuning models or training from scratc…☆153Updated 2 years ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆130Updated 3 years ago
- A Python package for intrinsic dimension estimation☆95Updated 3 months 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
- Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)☆48Updated 4 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆90Updated last year
- ☆17Updated 3 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated 2 years ago
- Last-layer Laplace approximation code examples☆83Updated 4 years ago
- An implementation of the BADGE batch active learning algorithm.☆210Updated last year