{"total":47,"rows":[{"id":"2207.07411","title":"Plex: Towards Reliability using Pretrained Large Model Extensions","created":"2022-07-15","cited_by_count":102,"area":null},{"id":"2302.13425","title":"A Survey on Uncertainty Quantification Methods for Deep Learning","created":"2023-02-26","cited_by_count":81,"area":null},{"id":"2404.11599","title":"Variational Bayesian Last Layers","created":"2024-04-17","cited_by_count":69,"area":null},{"id":"2207.09239","title":"Assaying Out-Of-Distribution Generalization in Transfer Learning","created":"2022-07-19","cited_by_count":53,"area":null},{"id":"2212.01758","title":"Improving Zero-shot Generalization and Robustness of Multi-modal Models","created":"2022-12-04","cited_by_count":45,"area":null},{"id":"2210.15452","title":"Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity","created":"2022-10-20","cited_by_count":25,"area":null},{"id":"2403.18910","title":"A Geometric Explanation of the Likelihood OOD Detection Paradox","created":"2024-03-27","cited_by_count":22,"area":null},{"id":"2302.12565","title":"Variational Linearized Laplace Approximation for Bayesian Deep Learning","created":"2023-02-24","cited_by_count":18,"area":null},{"id":"2405.04278","title":"Uncertainty Quantification Metrics for Deep Regression","created":"2024-05-07","cited_by_count":16,"area":null},{"id":"2402.01344","title":"Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks","created":"2024-02-02","cited_by_count":9,"area":null},{"id":"2412.15758","title":"Function Space Diversity for Uncertainty Prediction via Repulsive Last-Layer Ensembles","created":"2024-12-20","cited_by_count":8,"area":null},{"id":"2209.11960","title":"Raising the Bar on the Evaluation of Out-of-Distribution Detection","created":"2022-09-24","cited_by_count":7,"area":null},{"id":"2306.14658","title":"Beyond AUROC & co. for evaluating out-of-distribution detection performance","created":"2023-06-26","cited_by_count":7,"area":null},{"id":"2304.04042","title":"Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification","created":"2023-04-08","cited_by_count":6,"area":null},{"id":"2404.08981","title":"Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active Image Classification","created":"2024-04-13","cited_by_count":6,"area":null},{"id":"2307.00667","title":"Morse Neural Networks for Uncertainty Quantification","created":"2023-07-02","cited_by_count":4,"area":null},{"id":"2206.10911","title":"Influence of uncertainty estimation techniques on false-positive reduction in liver lesion detection","created":"2022-06-22","cited_by_count":3,"area":null},{"id":"2305.17063","title":"Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks","created":"2023-05-26","cited_by_count":3,"area":null},{"id":"2406.10775","title":"A Rate-Distortion View of Uncertainty Quantification","created":"2024-06-16","cited_by_count":3,"area":null},{"id":"2503.15583","title":"Efficient Post-Hoc Uncertainty Calibration via Variance-Based Smoothing","created":"2025-03-19","cited_by_count":3,"area":null},{"id":"2601.08064","title":"Calibration Is Not Enough: Evaluating Confidence Estimation Under Language Variations","created":"2026-01-12","cited_by_count":3,"area":null},{"id":"2210.06112","title":"Efficient Bayesian Updates for Deep Active Learning via Laplace Approximations","created":"2022-10-12","cited_by_count":2,"area":null},{"id":"2302.05807","title":"Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play","created":"2023-02-11","cited_by_count":2,"area":null},{"id":"2308.04588","title":"ScatterUQ: Interactive Uncertainty Visualizations for Multiclass Deep Learning Problems","created":"2023-08-08","cited_by_count":2,"area":null},{"id":"2312.04604","title":"Transferable Candidate Proposal with Bounded Uncertainty","created":"2023-12-07","cited_by_count":2,"area":null},{"id":"2412.04177","title":"Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning","created":"2024-12-05","cited_by_count":2,"area":null},{"id":"2502.01861","title":"Learning Hyperparameters via a Data-Emphasized Variational Objective","created":"2025-02-03","cited_by_count":2,"area":null},{"id":"2507.14919","title":"Old Rules in a New Game: Mapping Uncertainty Quantification to Quantum Machine Learning","created":"2025-07-20","cited_by_count":2,"area":null},{"id":"2507.15976","title":"Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models","created":"2025-07-21","cited_by_count":2,"area":null},{"id":"2601.21835","title":"Scalable Linearized Laplace Approximation via Surrogate Neural Kernel","created":"2026-01-29","cited_by_count":2,"area":null},{"id":"2408.03746","title":"Flexible Bayesian Last Layer Models Using Implicit Priors and Diffusion Posterior Sampling","created":"2024-08-07","cited_by_count":1,"area":null},{"id":"2410.20754","title":"Likelihood approximations via Gaussian approximate inference","created":"2024-10-28","cited_by_count":1,"area":null},{"id":"2605.31220","title":"Shared Doubt: Zero-Shot Cross-Lingual Confidence Estimation for Language Models","created":"2026-05-29","cited_by_count":1,"area":null},{"id":"2606.17513","title":"Geometry-Aware Post-Hoc Uncertainty Quantification in Operator Learning","created":"2026-06-16","cited_by_count":1,"area":null},{"id":"2404.12445","title":"Adaptive Catalyst Discovery Using Multicriteria Bayesian Optimization with Representation Learning","created":"2024-04-18","cited_by_count":0,"area":null},{"id":"2411.17571","title":"Uncertainty quantification for White Matter Hyperintensity segmentation detects silent failures and improves automated Fazekas quantification","created":"2024-11-26","cited_by_count":0,"area":null},{"id":"2501.00053","title":"Implementing Trust in Non-Small Cell Lung Cancer Diagnosis with a Conformalized Uncertainty-Aware AI Framework in Whole-Slide Images","created":"2024-12-28","cited_by_count":0,"area":null},{"id":"2501.17414","title":"Reqo: A Comprehensive Learning-Based Cost Model for Robust and Explainable Query Optimization","created":"2025-01-29","cited_by_count":0,"area":null},{"id":"2505.18526","title":"Scalable Deep Basis Kernel Gaussian Processes","created":"2025-05-24","cited_by_count":0,"area":null},{"id":"2508.00754","title":"A Simple and Effective Method for Uncertainty Quantification and OOD Detection","created":"2025-08-01","cited_by_count":0,"area":null},{"id":"2603.01750","title":"Practical Deep Heteroskedastic Regression","created":"2026-03-02","cited_by_count":0,"area":null},{"id":"2605.25616","title":"Courtroom Analogy: New Perspective on Uncertainty-Aware Classification","created":"2026-05-25","cited_by_count":0,"area":null},{"id":"2606.02876","title":"RRISE: Robust Radius Inference via a Surrogate Estimator","created":"2026-06-01","cited_by_count":0,"area":null},{"id":"2607.23856","title":"Covariance Last-Layer Ensembles: Function-Space Diversity for Efficient Uncertainty Quantification","created":"2026-07-26","cited_by_count":0,"area":null},{"id":"2607.28248","title":"Uncertainty quantification for trustworthy deep learning: Methods and measures","created":"2026-07-30","cited_by_count":0,"area":null},{"id":"2608.08398","title":"Estimating Uncertainty in Galaxy Morphology Classification","created":"2026-08-09","cited_by_count":0,"area":null},{"id":"2609.08620","title":"Flexible Spectral-Normalized Neural Gaussian Process for Dynamic Aperture Prediction","created":"2026-09-08","cited_by_count":0,"area":null}],"next_cursor":null}