Uncertainty Estimation

Uncertainty estimation in machine learning aims to quantify the reliability of model predictions, addressing the critical need for trustworthy AI systems. Current research focuses on improving uncertainty quantification across diverse model architectures, including Bayesian neural networks, ensembles, and novel methods like evidential deep learning and conformal prediction, often tailored to specific application domains (e.g., medical imaging, natural language processing). Accurate uncertainty estimation is crucial for responsible AI deployment, enabling better decision-making in high-stakes applications and fostering greater trust in AI-driven outcomes across various scientific and practical fields. This includes identifying unreliable predictions, improving model calibration, and mitigating issues like hallucinations in large language models.

Papers

November 13, 2023

November 5, 2023

Uncertainty Estimation for Safety-critical Scene Segmentation via Fine-grained Reward Maximization
Hongzheng Yang, Cheng Chen, Yueyao Chen, Markus Scheppach, Hon Chi Yip, Qi Dou
Fine Grained Uncertainty Estimation Vision Based Model Uncertainty Scene Segmentation Reward Ambiguity Surgical Scene Segmentation

November 1, 2023

A Robust Deep Learning Method with Uncertainty Estimation for the Pathological Classification of Renal Cell Carcinoma based on CT Images
Ni Yao, Hang Hu, Kaicong Chen, Chen Zhao, Yuan Guo, Boya Li, Jiaofen Nan, Yanting Li, Chuang Han, Fubao Zhu, Weihua Zhou, Li Tian
Deep Learning Uncertainty Estimation CT Image Robust Deep Renal Cell Carcinoma

October 31, 2023

Ensemble models outperform single model uncertainties and predictions for operator-learning of hypersonic flows
Victor J. Leon, Noah Ford, Honest Mrema, Jeffrey Gilbert, Alexander New
Human Prediction Uncertainty Quantification Uncertainty Estimation Operator Learning Ensemble Model Hypersonic Flow SciML Model

October 25, 2023

Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations
Tsai Hor Chan, Kin Wai Lau, Jiajun Shen, Guosheng Yin, Lequan Yu
High Dimensional Latent Representation Uncertainty Estimation Uncertainty Estimation Method Accurate Uncertainty Uncertainty Estimation Performance Adaptive Uncertainty

October 24, 2023

Guaranteed Coverage Prediction Intervals with Gaussian Process Regression
Harris Papadopoulos
Uncertainty Estimation Conformal Prediction Gaussian Process Regression Prediction Interval

October 23, 2023

UncertaintyPlayground: A Fast and Simplified Python Library for Uncertainty Estimation
Ilia Azizi
Uncertainty Estimation Pytorch Model Python Library

October 19, 2023

Be Bayesian by Attachments to Catch More Uncertainty
Shiyu Shen, Bin Pan, Tianyang Shi, Tao Li, Zhenwei Shi
Uncertainty Estimation Bayesian Neural Network Document Image Bayesian Structure State of the Art Uncertainty

October 15, 2023

Estimating Uncertainty in Multimodal Foundation Models using Public Internet Data
Shiladitya Dutta, Hongbo Wei, Lars van der Laan, Ahmed M. Alaa
Zero Shot Uncertainty Estimation Conformal Prediction Zero Shot Classification Available Datasets Multimodal Foundation Model Conformal Prediction Set

October 10, 2023

Deep Learning reconstruction with uncertainty estimation for $\gamma$ photon interaction in fast scintillator detectors
Geoffrey Daniel, Mohamed Bahi Yahiaoui, Claude Comtat, Sebastien Jan, Olga Kochebina, Jean-Marc Martinez, Viktoriya Sergeyeva, Viatcheslav Sharyy, Chi-Hsun Sung, Dominique Yvon
Uncertainty Estimation Physic Informed Deep Learning Gamma Ray Learning Based Reconstruction

October 2, 2023

Unified Uncertainty Calibration
Kamalika Chaudhuri, David Lopez-Paz
Uncertainty Estimation Epistemic Uncertainty Uncertainty Calibration Calibrated Uncertainty

September 28, 2023

Propagation and Attribution of Uncertainty in Medical Imaging Pipelines
Leonhard F. Feiner, Martin J. Menten, Kerstin Hammernik, Paul Hager, Wenqi Huang, Daniel Rueckert, Rickmer F. Braren, Georgios Kaissis
High Uncertainty Anticipation Uncertainty Estimation Source Attribution Fast Propagation Input Uncertainty Imaging Pipeline

September 19, 2023

Uncertainty Estimation in Instance Segmentation with Star-convex Shapes
Qasim M. K. Siddiqui, Sebastian Starke, Peter Steinbach
Instance Segmentation Uncertainty Estimation Convex Set Prediction Uncertainty Uncertainty Score

September 5, 2023

August 30, 2023

Interactively Robot Action Planning with Uncertainty Analysis and Active Questioning by Large Language Model
Kazuki Hori, Kanata Suzuki, Tetsuya Ogata
Large Language Model Natural Language Uncertainty Estimation Robot Action Robot Planning Complex Robotic Task

August 22, 2023

Uncertainty Estimation of Transformers' Predictions via Topological Analysis of the Attention Matrices
Elizaveta Kostenok, Daniil Cherniavskii, Alexey Zaytsev
Deep Learning Model Transformer Megatron Decepticons Human Prediction Attention Mechanism Uncertainty Estimation Topological Feature Attention Matrix Topological Analysis

August 14, 2023

Probabilistic MIMO U-Net: Efficient and Accurate Uncertainty Estimation for Pixel-wise Regression
Anton Baumann, Thomas Roßberg, Michael Schmitt
Deep Neural Network Uncertainty Estimation U Net Accurate Uncertainty Pixel Wise Regression

August 11, 2023

Comparing the quality of neural network uncertainty estimates for classification problems
Daniel Ries, Joshua Michalenko, Tyler Ganter, Rashad Imad-Fayez Baiyasi, Jason Adams
Neural Network Uncertainty Quantification Uncertainty Estimation Bayesian Neural Network Quality Issue Deep Ensemble Classification Problem

Uncertainty Estimation

Papers

Uncertainty estimation in satellite precipitation interpolation with machine learning

LM-Polygraph: Uncertainty Estimation for Language Models

Uncertainty Estimation for Safety-critical Scene Segmentation via Fine-grained Reward Maximization

A Robust Deep Learning Method with Uncertainty Estimation for the Pathological Classification of Renal Cell Carcinoma based on CT Images

Ensemble models outperform single model uncertainties and predictions for operator-learning of hypersonic flows

Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations

Guaranteed Coverage Prediction Intervals with Gaussian Process Regression

UncertaintyPlayground: A Fast and Simplified Python Library for Uncertainty Estimation

Be Bayesian by Attachments to Catch More Uncertainty

Estimating Uncertainty in Multimodal Foundation Models using Public Internet Data

Deep Learning reconstruction with uncertainty estimation for $\gamma$ photon interaction in fast scintillator detectors

Unified Uncertainty Calibration

Propagation and Attribution of Uncertainty in Medical Imaging Pipelines

Uncertainty Estimation in Instance Segmentation with Star-convex Shapes

Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning

Sparse Function-space Representation of Neural Networks

Interactively Robot Action Planning with Uncertainty Analysis and Active Questioning by Large Language Model

Uncertainty Estimation of Transformers' Predictions via Topological Analysis of the Attention Matrices

Probabilistic MIMO U-Net: Efficient and Accurate Uncertainty Estimation for Pixel-wise Regression

Comparing the quality of neural network uncertainty estimates for classification problems