| A Rate-Distortion View of Uncertainty Quantification | Jun 16, 2024 | Gaussian ProcessesOut of Distribution (OOD) Detection | CodeCode Available | 1 | 5 |
| PDE-NetGen 1.0: from symbolic PDE representations of physical processes to trainable neural network representations | Feb 3, 2020 | Uncertainty Quantification | CodeCode Available | 1 | 5 |
| Conformal Prediction with Large Language Models for Multi-Choice Question Answering | May 28, 2023 | Conformal PredictionMultiple-choice | CodeCode Available | 1 | 5 |
| Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification | Nov 11, 2024 | BenchmarkingImage Segmentation | CodeCode Available | 1 | 5 |
| Conformal Prediction with Missing Values | Jun 5, 2023 | Conformal PredictionData Augmentation | CodeCode Available | 1 | 5 |
| alpha-Deep Probabilistic Inference (alpha-DPI): efficient uncertainty quantification from exoplanet astrometry to black hole feature extraction | Jan 21, 2022 | Uncertainty QuantificationVariational Inference | CodeCode Available | 1 | 5 |
| Enhancing Uncertainty Quantification in Drug Discovery with Censored Regression Labels | Sep 6, 2024 | Drug Discoveryregression | CodeCode Available | 1 | 5 |
| coverforest: Conformal Predictions with Random Forest in Python | Jan 24, 2025 | Conformal PredictionPrediction | CodeCode Available | 1 | 5 |
| POINT^2: A Polymer Informatics Training and Testing Database | Mar 30, 2025 | Uncertainty Quantification | CodeCode Available | 1 | 5 |
| Point-DeepONet: A Deep Operator Network Integrating PointNet for Nonlinear Analysis of Non-Parametric 3D Geometries and Load Conditions | Dec 24, 2024 | Operator learningUncertainty Quantification | CodeCode Available | 1 | 5 |
| Posterior Inference with Diffusion Models for High-dimensional Black-box Optimization | Feb 24, 2025 | Bayesian OptimizationUncertainty Quantification | CodeCode Available | 1 | 5 |
| Posterior Sampling for Deep Reinforcement Learning | Apr 30, 2023 | Computational EfficiencyDeep Reinforcement Learning | CodeCode Available | 1 | 5 |
| CoT-UQ: Improving Response-wise Uncertainty Quantification in LLMs with Chain-of-Thought | Feb 24, 2025 | Mathematical ReasoningMisinformation | CodeCode Available | 1 | 5 |
| Post-hoc Uncertainty Learning using a Dirichlet Meta-Model | Dec 14, 2022 | image-classificationImage Classification | CodeCode Available | 1 | 5 |
| Enabling Uncertainty Estimation in Iterative Neural Networks | Mar 25, 2024 | Bayesian OptimizationOut-of-Distribution Detection | CodeCode Available | 1 | 5 |
| Principal Uncertainty Quantification with Spatial Correlation for Image Restoration Problems | May 17, 2023 | ColorizationComputational Efficiency | CodeCode Available | 1 | 5 |
| Probabilistic 3D segmentation for aleatoric uncertainty quantification in full 3D medical data | May 1, 2023 | Decision MakingLung Nodule Segmentation | CodeCode Available | 1 | 5 |
| Probabilistic Circuits That Know What They Don't Know | Feb 13, 2023 | Uncertainty Quantification | CodeCode Available | 1 | 5 |
| Edge Tracing using Gaussian Process Regression | Nov 5, 2021 | regressionUncertainty Quantification | CodeCode Available | 1 | 5 |
| Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization | Dec 15, 2021 | scoring ruleUncertainty Quantification | CodeCode Available | 1 | 5 |
| A Simple Baseline for Bayesian Uncertainty in Deep Learning | Feb 7, 2019 | Bayesian InferenceDeep Learning | CodeCode Available | 1 | 5 |
| Data-Driven Autoencoder Numerical Solver with Uncertainty Quantification for Fast Physical Simulations | Dec 2, 2023 | Active LearningGaussian Processes | CodeCode Available | 1 | 5 |
| A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification | Jul 15, 2021 | Conformal PredictionDeep Reinforcement Learning | CodeCode Available | 1 | 5 |
| Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling | Nov 15, 2023 | Uncertainty Quantification | CodeCode Available | 1 | 5 |
| Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification | Dec 4, 2020 | Bayesian InferenceDecision Making Under Uncertainty | CodeCode Available | 1 | 5 |
| Randomized Physics-Informed Neural Networks for Bayesian Data Assimilation | Jul 5, 2024 | Stochastic OptimizationUncertainty Quantification | CodeCode Available | 1 | 5 |
| Error-quantified Conformal Inference for Time Series | Feb 2, 2025 | PredictionTime Series | CodeCode Available | 1 | 5 |
| Dropout Injection at Test Time for Post Hoc Uncertainty Quantification in Neural Networks | Feb 6, 2023 | Crowd CountingUncertainty Quantification | CodeCode Available | 1 | 5 |
| A Head to Predict and a Head to Question: Pre-trained Uncertainty Quantification Heads for Hallucination Detection in LLM Outputs | May 13, 2025 | HallucinationUncertainty Quantification | CodeCode Available | 1 | 5 |
| Robust Uncertainty Quantification Using Conformalised Monte Carlo Prediction | Aug 18, 2023 | Conformal PredictionDecision Making | CodeCode Available | 1 | 5 |
| A Hierarchical Spatial Transformer for Massive Point Samples in Continuous Space | Sep 21, 2023 | GPURepresentation Learning | CodeCode Available | 1 | 5 |
| Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation | Sep 12, 2023 | Image SegmentationMedical Image Segmentation | CodeCode Available | 1 | 5 |
| Deep Generative Classification of Blood Cell Morphology | Aug 16, 2024 | Anomaly DetectionClassification | CodeCode Available | 1 | 5 |
| Deep Gaussian Process Emulation using Stochastic Imputation | Jul 4, 2021 | Gaussian ProcessesImputation | CodeCode Available | 1 | 5 |
| Deep learning observables in computational fluid dynamics | Mar 7, 2019 | Deep LearningEfficient Neural Network | CodeCode Available | 1 | 5 |
| Scaling Hamiltonian Monte Carlo Inference for Bayesian Neural Networks with Symmetric Splitting | Oct 14, 2020 | GPUUncertainty Quantification | CodeCode Available | 1 | 5 |
| AutoIP: A United Framework to Integrate Physics into Gaussian Processes | Feb 24, 2022 | Gaussian ProcessesUncertainty Quantification | CodeCode Available | 1 | 5 |
| Semantic Density: Uncertainty Quantification for Large Language Models through Confidence Measurement in Semantic Space | May 22, 2024 | MisinformationQuestion Answering | CodeCode Available | 1 | 5 |
| Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging | Oct 27, 2020 | compressed sensingImage Reconstruction | CodeCode Available | 1 | 5 |
| Dual Accuracy-Quality-Driven Neural Network for Prediction Interval Generation | Dec 13, 2022 | PredictionPrediction Intervals | CodeCode Available | 1 | 5 |
| Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification | Feb 2, 2018 | Uncertainty Quantification | CodeCode Available | 1 | 5 |
| Uncertainty Estimation Using a Single Deep Deterministic Neural Network | Mar 4, 2020 | Out-of-Distribution DetectionUncertainty Quantification | CodeCode Available | 1 | 5 |
| Disentangling Uncertainty in Machine Translation Evaluation | Apr 13, 2022 | Machine TranslationPrediction | CodeCode Available | 1 | 5 |
| Simulator-Based Inference with Waldo: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems | May 31, 2022 | PredictionUncertainty Quantification | CodeCode Available | 1 | 5 |
| DiffLoad: Uncertainty Quantification in Electrical Load Forecasting with the Diffusion Model | May 31, 2023 | Decision Makingenergy management | CodeCode Available | 1 | 5 |
| DIFR3CT: Latent Diffusion for Probabilistic 3D CT Reconstruction from Few Planar X-Rays | Aug 27, 2024 | AnatomyComputed Tomography (CT) | CodeCode Available | 1 | 5 |
| Author Clustering and Topic Estimation for Short Texts | Jun 15, 2021 | ClusteringUncertainty Quantification | CodeCode Available | 1 | 5 |
| Stochastic Optimal Control as Approximate Input Inference | Oct 7, 2019 | Uncertainty Quantification | CodeCode Available | 1 | 5 |
| Distribution-free binary classification: prediction sets, confidence intervals and calibration | Jun 18, 2020 | Binary ClassificationClassification | CodeCode Available | 1 | 5 |
| Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning | Jun 6, 2015 | Bayesian InferenceDeep Reinforcement Learning | CodeCode Available | 1 | 5 |
