Saved in:
| Main Authors: | Torbunov, Dmitrii, Ren, Yihui, Wu, Lijun, Zhu, Yimei |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.17224 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
CDI: Copyrighted Data Identification in Diffusion Models
by: Dubiński, Jan, et al.
Published: (2024)
by: Dubiński, Jan, et al.
Published: (2024)
Diffusion Model-based Parameter Estimation in Dynamic Power Systems
by: Zhu, Feiqin, et al.
Published: (2024)
by: Zhu, Feiqin, et al.
Published: (2024)
Uncertainty Quantification for Physics-Informed Neural Networks with Extended Fiducial Inference
by: Shih, Frank, et al.
Published: (2025)
by: Shih, Frank, et al.
Published: (2025)
Reliable Trajectory Prediction and Uncertainty Quantification with Conditioned Diffusion Models
by: Neumeier, Marion, et al.
Published: (2024)
by: Neumeier, Marion, et al.
Published: (2024)
Uncertainty Quantification of Data Shapley via Statistical Inference
by: Wu, Mengmeng, et al.
Published: (2024)
by: Wu, Mengmeng, et al.
Published: (2024)
Conditional Uncertainty Quantification for Tensorized Topological Neural Networks
by: Wu, Yujia, et al.
Published: (2024)
by: Wu, Yujia, et al.
Published: (2024)
Rapid Parameter Inference with Uncertainty Quantification for a Radiological Plume Source Identification Problem
by: Edwards, Christopher, et al.
Published: (2025)
by: Edwards, Christopher, et al.
Published: (2025)
AutoSizer: Automatic Sizing of Analog and Mixed-Signal Circuits via Large Language Model (LLM) Agents
by: Yu, Xi, et al.
Published: (2026)
by: Yu, Xi, et al.
Published: (2026)
CoDiCast: Conditional Diffusion Model for Global Weather Prediction with Uncertainty Quantification
by: Shi, Jimeng, et al.
Published: (2024)
by: Shi, Jimeng, et al.
Published: (2024)
Joint Parameter and Parameterization Inference with Uncertainty Quantification through Differentiable Programming
by: Qu, Yongquan, et al.
Published: (2024)
by: Qu, Yongquan, et al.
Published: (2024)
Reimagining Parameter Space Exploration with Diffusion Models
by: Zhang, Lijun, et al.
Published: (2025)
by: Zhang, Lijun, et al.
Published: (2025)
Neural Conditional Probability for Uncertainty Quantification
by: Kostic, Vladimir R., et al.
Published: (2024)
by: Kostic, Vladimir R., et al.
Published: (2024)
FedSI: Federated Subnetwork Inference for Efficient Uncertainty Quantification
by: Chen, Hui, et al.
Published: (2024)
by: Chen, Hui, et al.
Published: (2024)
Zero-Shot Uncertainty Quantification using Diffusion Probabilistic Models
by: Shu, Dule, et al.
Published: (2024)
by: Shu, Dule, et al.
Published: (2024)
Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference
by: Reiser, Philipp, et al.
Published: (2023)
by: Reiser, Philipp, et al.
Published: (2023)
Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs
by: Margossian, Charles C., et al.
Published: (2024)
by: Margossian, Charles C., et al.
Published: (2024)
Parameter-Free Clustering via Self-Supervised Consensus Maximization (Extended Version)
by: Zhang, Lijun, et al.
Published: (2025)
by: Zhang, Lijun, et al.
Published: (2025)
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)
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)
Spatial Uncertainty Quantification in Wildfire Forecasting for Climate-Resilient Emergency Planning
by: Chakravarty, Aditya
Published: (2025)
by: Chakravarty, Aditya
Published: (2025)
DiffLoad: Uncertainty Quantification in Electrical Load Forecasting with the Diffusion Model
by: Wang, Zhixian, et al.
Published: (2023)
by: Wang, Zhixian, et al.
Published: (2023)
Minimal Ranks, Maximum Confidence: Parameter-efficient Uncertainty Quantification for LoRA
by: Marszałek, Patryk, et al.
Published: (2025)
by: Marszałek, Patryk, et al.
Published: (2025)
IE2Video: Adapting Pretrained Diffusion Models for Event-Based Video Reconstruction
by: Torbunov, Dmitrii, et al.
Published: (2025)
by: Torbunov, Dmitrii, et al.
Published: (2025)
Tackling Fake Forgetting through Uncertainty Quantification
by: Shi, Yingdan, et al.
Published: (2025)
by: Shi, Yingdan, et al.
Published: (2025)
Quantile Regression, Variational Autoencoders, and Diffusion Models for Uncertainty Quantification: A Spatial Analysis of Sub-seasonal Wind Speed Prediction
by: Tian, Ganglin, et al.
Published: (2025)
by: Tian, Ganglin, et al.
Published: (2025)
Diffusion Transformers for Imputation: Statistical Efficiency and Uncertainty Quantification
by: Ye, Zeqi, et al.
Published: (2025)
by: Ye, Zeqi, et al.
Published: (2025)
Quantification of Uncertainties in Probabilistic Deep Neural Network by Implementing Boosting of Variational Inference
by: Bera, Pavia, et al.
Published: (2025)
by: Bera, Pavia, et al.
Published: (2025)
Light-Weight Diffusion Multiplier and Uncertainty Quantification for Fourier Neural Operators
by: Matveev, Albert, et al.
Published: (2025)
by: Matveev, Albert, et al.
Published: (2025)
Uncertainty Quantification in PINNs for Turbulent Flows: Bayesian Inference and Repulsive Ensembles
by: Shukla, Khemraj, et al.
Published: (2026)
by: Shukla, Khemraj, et al.
Published: (2026)
On the Uncertainty Quantification Ability of Tabular Foundation Models
by: Johnson, Tyler R., et al.
Published: (2026)
by: Johnson, Tyler R., et al.
Published: (2026)
Multi-fidelity Parameter Estimation Using Conditional Diffusion Models
by: Tatsuoka, Caroline, et al.
Published: (2025)
by: Tatsuoka, Caroline, et al.
Published: (2025)
Predicting Critical Heat Flux with Uncertainty Quantification and Domain Generalization Using Conditional Variational Autoencoders and Deep Neural Networks
by: Alsafadi, Farah, et al.
Published: (2024)
by: Alsafadi, Farah, et al.
Published: (2024)
GenAI4UQ: A Software for Inverse Uncertainty Quantification Using Conditional Generative Models
by: Fan, Ming, et al.
Published: (2024)
by: Fan, Ming, et al.
Published: (2024)
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)
Statistical Inference in Tensor Completion: Optimal Uncertainty Quantification and Statistical-to-Computational Gaps
by: Ma, Wanteng, et al.
Published: (2024)
by: Ma, Wanteng, et al.
Published: (2024)
Posterior Uncertainty Quantification in Neural Networks using Data Augmentation
by: Wu, Luhuan, et al.
Published: (2024)
by: Wu, Luhuan, et al.
Published: (2024)
Epistemic Wrapping for Uncertainty Quantification
by: Sultana, Maryam, et al.
Published: (2025)
by: Sultana, Maryam, et al.
Published: (2025)
EvRT-DETR: Latent Space Adaptation of Image Detectors for Event-based Vision
by: Torbunov, Dmitrii, et al.
Published: (2024)
by: Torbunov, Dmitrii, et al.
Published: (2024)
Towards Uncertainty Quantification in Generative Model Learning
by: Morales, Giorgio, et al.
Published: (2025)
by: Morales, Giorgio, et al.
Published: (2025)
Towards Intrinsically Calibrated Uncertainty Quantification in Industrial Data-Driven Models via Diffusion Sampler
by: Ma, Yiran, et al.
Published: (2026)
by: Ma, Yiran, et al.
Published: (2026)
Similar Items
-
CDI: Copyrighted Data Identification in Diffusion Models
by: Dubiński, Jan, et al.
Published: (2024) -
Diffusion Model-based Parameter Estimation in Dynamic Power Systems
by: Zhu, Feiqin, et al.
Published: (2024) -
Uncertainty Quantification for Physics-Informed Neural Networks with Extended Fiducial Inference
by: Shih, Frank, et al.
Published: (2025) -
Reliable Trajectory Prediction and Uncertainty Quantification with Conditioned Diffusion Models
by: Neumeier, Marion, et al.
Published: (2024) -
Uncertainty Quantification of Data Shapley via Statistical Inference
by: Wu, Mengmeng, et al.
Published: (2024)