Multivariate and Online Transfer Learning with Uncertainty Quantification
Fuente:
arXiv
Saved in:
| Main Authors: | Hickey, Jimmy, Williams, Jonathan P., Reich, Brian J., Hector, Emily C. |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Multivariate and Online Transfer Learning With Uncertainty Quantification
by: Jimmy Hickey, et al.
Published: (2026)
by: Jimmy Hickey, et al.
Published: (2026)
On the Need to Align Intent and Implementation in Uncertainty Quantification for Machine Learning
by: Trivedi, Shubhendu, et al.
Published: (2025)
by: Trivedi, Shubhendu, et al.
Published: (2025)
Self-Labeling in Multivariate Causality and Quantification for Adaptive Machine Learning
by: Ren, Yutian, et al.
Published: (2024)
by: Ren, Yutian, et al.
Published: (2024)
Uncertainty Quantification With Multiple Sources
by: Ying, Mufang, et al.
Published: (2024)
by: Ying, Mufang, et al.
Published: (2024)
Accurate Large-sample Uncertainty Quantification using Stochastic Gradient Markov Chain Monte Carlo
by: Wang, Yu, et al.
Published: (2026)
by: Wang, Yu, et al.
Published: (2026)
HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation
by: Su, Weijie J., et al.
Published: (2018)
by: Su, Weijie J., et al.
Published: (2018)
Interventional Processes for Causal Uncertainty Quantification
by: Dance, Hugh, et al.
Published: (2024)
by: Dance, Hugh, et al.
Published: (2024)
Smooth Sailing: Lipschitz-Driven Uncertainty Quantification for Spatial Association
by: Burt, David R., et al.
Published: (2025)
by: Burt, David R., et al.
Published: (2025)
Contextual Online Uncertainty-Aware Preference Learning for Human Feedback
by: Lu, Nan, et al.
Published: (2025)
by: Lu, Nan, et al.
Published: (2025)
When the whole is greater than the sum of its parts: Scaling black-box inference to large data settings through divide-and-conquer
by: Hector, Emily C., et al.
Published: (2024)
by: Hector, Emily C., et al.
Published: (2024)
Neural Conditional Probability for Uncertainty Quantification
by: Kostic, Vladimir R., et al.
Published: (2024)
by: Kostic, Vladimir R., et al.
Published: (2024)
Fully Bayesian Spectral Clustering and Benchmarking with Uncertainty Quantification for Small Area Estimation
by: Fúquene-Patiño, Jairo
Published: (2025)
by: Fúquene-Patiño, Jairo
Published: (2025)
Fast Uncertainty Quantification for Kernel-Based Estimators in Large-Scale Causal Inference
by: Kosko, Matthew, et al.
Published: (2026)
by: Kosko, Matthew, et al.
Published: (2026)
Uncertainty Quantification of MLE for Entity Ranking with Covariates
by: Fan, Jianqing, et al.
Published: (2022)
by: Fan, Jianqing, et al.
Published: (2022)
Amortized Bayesian Local Interpolation NetworK: Fast covariance parameter estimation for Gaussian Processes
by: Feng, Brandon R., et al.
Published: (2024)
by: Feng, Brandon R., et al.
Published: (2024)
Efficient Online Variational Estimation via Monte Carlo Sampling
by: Chagneux, Mathis, et al.
Published: (2026)
by: Chagneux, Mathis, et al.
Published: (2026)
Understanding the Trade-offs in Accuracy and Uncertainty Quantification: Architecture and Inference Choices in Bayesian Neural Networks
by: Sheinkman, Alisa, et al.
Published: (2025)
by: Sheinkman, Alisa, et al.
Published: (2025)
Model-Free Kernel Conformal Depth Measures Algorithm for Uncertainty Quantification in Regression Models in Separable Hilbert Spaces
by: Matabuena, Marcos, et al.
Published: (2025)
by: Matabuena, Marcos, et al.
Published: (2025)
Bin-Conditional Conformal Prediction of Fatalities from Armed Conflict
by: Randahl, David, et al.
Published: (2024)
by: Randahl, David, et al.
Published: (2024)
Adaptive Uncertainty Quantification for Generative AI
by: Kim, Jungeum, et al.
Published: (2024)
by: Kim, Jungeum, et al.
Published: (2024)
Conformal and kNN Predictive Uncertainty Quantification Algorithms in Metric Spaces
by: Lugosi, Gábor, et al.
Published: (2025)
by: Lugosi, Gábor, et al.
Published: (2025)
PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Framework
by: Agarwal, Abhineet, et al.
Published: (2025)
by: Agarwal, Abhineet, et al.
Published: (2025)
STACI: Spatio-Temporal Aleatoric Conformal Inference
by: Feng, Brandon R., et al.
Published: (2025)
by: Feng, Brandon R., et al.
Published: (2025)
Dynamical System Identification, Model Selection and Model Uncertainty Quantification by Bayesian Inference
by: Niven, Robert K., et al.
Published: (2024)
by: Niven, Robert K., et al.
Published: (2024)
"Over-optimizing" for Normality: Budget-constrained Uncertainty Quantification for Contextual Decision-making
by: Wang, Yanyuan, et al.
Published: (2025)
by: Wang, Yanyuan, et al.
Published: (2025)
Calibrated Multivariate Regression with Localized PIT Mappings
by: Kock, Lucas, et al.
Published: (2024)
by: Kock, Lucas, et al.
Published: (2024)
Uncertainty Quantification for Prior-Data Fitted Networks using Martingale Posteriors
by: Nagler, Thomas, et al.
Published: (2025)
by: Nagler, Thomas, et al.
Published: (2025)
Imputation Uncertainty in Interpretable Machine Learning Methods
by: Golchian, Pegah, et al.
Published: (2025)
by: Golchian, Pegah, et al.
Published: (2025)
Deep Learning of Multivariate Extremes via a Geometric Representation
by: Murphy-Barltrop, Callum J. R., et al.
Published: (2024)
by: Murphy-Barltrop, Callum J. R., et al.
Published: (2024)
Smoothness Adaptive Hypothesis Transfer Learning
by: Lin, Haotian, et al.
Published: (2024)
by: Lin, Haotian, et al.
Published: (2024)
Spatial Transfer Learning with Simple MLP
by: Yang, Hongjian
Published: (2024)
by: Yang, Hongjian
Published: (2024)
Transfer Learning for Kernel-based Regression
by: Wang, Chao, et al.
Published: (2023)
by: Wang, Chao, et al.
Published: (2023)
How Many Human Survey Respondents is a Large Language Model Worth? An Uncertainty Quantification Perspective
by: Huang, Chengpiao, et al.
Published: (2025)
by: Huang, Chengpiao, et al.
Published: (2025)
Transfer Learning of CATE with Kernel Ridge Regression
by: Kim, Seok-Jin, et al.
Published: (2025)
by: Kim, Seok-Jin, et al.
Published: (2025)
MMM: Clustering Multivariate Longitudinal Mixed-type Data
by: Amato, Francesco, et al.
Published: (2025)
by: Amato, Francesco, et al.
Published: (2025)
Distributed model building and recursive integration for big spatial data modeling
by: Hector, Emily C., et al.
Published: (2023)
by: Hector, Emily C., et al.
Published: (2023)
Estimating Covariate Effects on Functional Connectivity using Voxel-Level fMRI Data
by: Zhao, Wei, et al.
Published: (2025)
by: Zhao, Wei, et al.
Published: (2025)
Improving Active Learning with a Bayesian Representation of Epistemic Uncertainty
by: Thomas, Jake, et al.
Published: (2024)
by: Thomas, Jake, et al.
Published: (2024)
Data-Driven Knowledge Transfer in Batch $Q^*$ Learning
by: Chen, Elynn, et al.
Published: (2024)
by: Chen, Elynn, et al.
Published: (2024)
Assessing Electricity Service Unfairness with Transfer Counterfactual Learning
by: Wei, Song, et al.
Published: (2023)
by: Wei, Song, et al.
Published: (2023)
Similar Items
-
Multivariate and Online Transfer Learning With Uncertainty Quantification
by: Jimmy Hickey, et al.
Published: (2026) -
On the Need to Align Intent and Implementation in Uncertainty Quantification for Machine Learning
by: Trivedi, Shubhendu, et al.
Published: (2025) -
Self-Labeling in Multivariate Causality and Quantification for Adaptive Machine Learning
by: Ren, Yutian, et al.
Published: (2024) -
Uncertainty Quantification With Multiple Sources
by: Ying, Mufang, et al.
Published: (2024) -
Accurate Large-sample Uncertainty Quantification using Stochastic Gradient Markov Chain Monte Carlo
by: Wang, Yu, et al.
Published: (2026)