Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

Natural Gradient Boosting for Probabilistic Prediction

A Library for Uncertainty Quantification.

UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination detection

An extension of XGBoost to probabilistic modelling

A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch

👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.

An extension of LightGBM to probabilistic modelling

[CVPR 2024 Award Candidate] Producing and Leveraging Online Map Uncertainty in Trajectory Prediction

CVPR 2020 - On the uncertainty of self-supervised monocular depth estimation

[ICCV 2021 Oral] Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation

Quantile Regression Forests compatible with scikit-learn.

[CVPR 2022 Oral] Multi-View Depth Estimation by Fusing Single-View Depth Probability with Multi-View Geometry

[CVPR 2024 Oral, Best Paper Award Candidate] Official repository of "PaSCo: Urban 3D Panoptic Scene Completion with Uncertainty Awareness"

GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation [IJCV2023]

[ICCV'23] Sparse Sampling Transformer with Uncertainty-Driven Ranking for Unified Removal of Raindrops and Rain Streaks

Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.

Official implementation of "Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision", CVPR Workshops 2020.

An Automatic Differentiation-based Waveform Inversion Framework Implemented in PyTorch.

Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR 2021).