Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
- Updated
Mar 5, 2025 - Python
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
Natural Gradient Boosting for Probabilistic Prediction
UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination detection
A Library for Uncertainty Quantification.
An extension of XGBoost to probabilistic modelling
👋 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
Quantile Regression Forests compatible with scikit-learn.
[ICCV 2021 Oral] Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation
CVPR 2020 - On the uncertainty of self-supervised monocular depth estimation
[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]
An Automatic Differentiation-based Waveform Inversion Framework Implemented in PyTorch.
[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.
Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR 2021).
Official Implementation of "Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions" (ICLR, 2022)
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