:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Amouzou, Isaac, Lee, Ben Seiyon
Format:	Preprint
Published:	2026
Subjects:	Computation Machine Learning
Online Access:	https://arxiv.org/abs/2605.16570
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

REX-SUB: A Scalable Subsampling Strategy for Modeling Large Spatial Datasets
by: Rios, Nicholas, et al.
Published: (2026)

A Scalable Variational Bayes Approach for Fitting Non-Conjugate Spatial Generalized Linear Mixed Models via Basis Expansions
by: Lee, Jin Hyung, et al.
Published: (2025)

Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning
by: Lehmann, Nils, et al.
Published: (2024)

Strategic Geosteering Workflow with Uncertainty Quantification and Deep Learning: A Case Study on the Goliat Field
by: Rammay, Muzammil Hussain, et al.
Published: (2022)

Self-Improving Interference Management Based on Deep Learning With Uncertainty Quantification
by: Lee, Hyun-Suk, et al.
Published: (2024)

A Survey on Uncertainty Quantification Methods for Deep Learning
by: He, Wenchong, et al.
Published: (2023)

Torch-Uncertainty: A Deep Learning Framework for Uncertainty Quantification
by: Lafage, Adrien, et al.
Published: (2025)

Uncertainty Quantification for In-Context Learning of Large Language Models
by: Ling, Chen, et al.
Published: (2024)

Uncertainty Quantification for Deep Learning
by: van Leeuwen, Peter Jan, et al.
Published: (2024)

Identifiable Object Representations under Spatial Ambiguities
by: Kori, Avinash, et al.
Published: (2025)

Automated Labeling of Intracranial Arteries with Uncertainty Quantification Using Deep Learning
by: Bisbal, Javier, et al.
Published: (2025)

Constraint-Aware Neurosymbolic Uncertainty Quantification with Bayesian Deep Learning for Scientific Discovery
by: Alam, Shahnawaz, et al.
Published: (2026)

Uncertainty Quantification in Detecting Choroidal Metastases on MRI via Evolutionary Strategies
by: McRae-Posani, Bala, et al.
Published: (2024)

Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review
by: de Jong, Ivo Pascal, et al.
Published: (2023)

The Consistency Hypothesis in Uncertainty Quantification for Large Language Models
by: Xiao, Quan, et al.
Published: (2025)

Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?
by: Shen, Maohao, et al.
Published: (2024)

Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs
by: Margossian, Charles C., et al.
Published: (2024)

Hyperparameters in Continual Learning: A Reality Check
by: Cha, Sungmin, et al.
Published: (2024)

Towards Better Understanding of In-Context Learning Ability from In-Context Uncertainty Quantification
by: Liu, Shang, et al.
Published: (2024)

Uncertainty Quantification Metrics for Deep Regression
by: Lind, Simon Kristoffersson, et al.
Published: (2024)

Uncertainty as Feature Gaps: Epistemic Uncertainty Quantification of LLMs in Contextual Question-Answering
by: Bakman, Yavuz, et al.
Published: (2025)

Generative Bayesian Hyperparameter Tuning
by: Lopes, Hedibert, et al.
Published: (2025)

Enhancing Multi-Label Thoracic Disease Diagnosis with Deep Ensemble-Based Uncertainty Quantification
by: Laksara, Yasiru, et al.
Published: (2025)

Tuning the Tuner: Introducing Hyperparameter Optimization for Auto-Tuning
by: Willemsen, Floris-Jan, et al.
Published: (2025)

Flow Matching with Uncertainty Quantification and Guidance
by: Han, Juyeop, et al.
Published: (2026)

Calibrated Physics-Informed Uncertainty Quantification
by: Gopakumar, Vignesh, et al.
Published: (2025)

Multi-level Monte Carlo Dropout for Efficient Uncertainty Quantification
by: Pim, Aaron, et al.
Published: (2026)

Estimating Semantic Alphabet Size for LLM Uncertainty Quantification
by: McCabe, Lucas H., et al.
Published: (2025)

Uncertainty Quantification in Graph Neural Networks with Shallow Ensembles
by: Vinchurkar, Tirtha, et al.
Published: (2025)

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning
by: Suurmeijer, Joris, et al.
Published: (2025)

Uncertainty Quantification via Stable Distribution Propagation
by: Petersen, Felix, et al.
Published: (2024)

A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation
by: Valiuddin, M. M. A., et al.
Published: (2024)

Large Language Model Enhanced Particle Swarm Optimization for Hyperparameter Tuning for Deep Learning Models
by: Hameed, Saad, et al.
Published: (2025)

Examining the Robustness of Homogeneity Bias to Hyperparameter Adjustments in GPT-4
by: Lee, Messi H. J.
Published: (2025)

A Class of Models for Large Zero-inflated Spatial Data
by: Lee, Ben Seiyon, et al.
Published: (2023)

Uncertainty Quantification of Deep Learning for Spatiotemporal Data: Challenges and Opportunities
by: He, Wenchong, et al.
Published: (2023)

Uncertainty Quantification for Surface Ozone Emulators using Deep Learning
by: Doerksen, Kelsey, et al.
Published: (2025)

Uncertainty Quantification for Machine Learning-Based Prediction: A Polynomial Chaos Expansion Approach for Joint Model and Input Uncertainty Propagation
by: Du, Xiaoping
Published: (2025)

Hyperparameter Selection in Continual Learning
by: Lee, Thomas L., et al.
Published: (2024)

Human-AI Collaborative Uncertainty Quantification
by: Noorani, Sima, et al.
Published: (2025)