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Uncertainty Quantification

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Showing 751–800 of 2366 papers

TitleStatusHype
Variance-Aware Linear UCB with Deep Representation for Neural Contextual BanditsCode0
Game-Theoretic Defenses for Robust Conformal Prediction Against Adversarial Attacks in Medical Imaging—0
Uncertainty Prediction Neural Network (UpNet): Embedding Artificial Neural Network in Bayesian Inversion Framework to Quantify the Uncertainty of Remote Sensing RetrievalCode0
Multi-model Ensemble Conformal Prediction in Dynamic EnvironmentsCode0
Uncertainty Quantification for Clinical Outcome Predictions with (Large) Language Models—0
Modeling Uncertainty in 3D Gaussian Splatting through Continuous Semantic Splatting—0
Stein Variational Newton Neural Network EnsemblesCode0
Targeted Learning for Variable Importance—0
Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI—0
Strategic Conformal Prediction—0
DSDE: Using Proportion Estimation to Improve Model Selection for Out-of-Distribution Detection—0
Adaptive Conformal Inference by Particle Filtering under Hidden Markov Models—0
FISHing in Uncertainty: Synthetic Contrastive Learning for Genetic Aberration DetectionCode0
Conformalized Prediction of Post-Fault Voltage Trajectories Using Pre-trained and Finetuned Attention-Driven Neural Operators—0
State- and context-dependent robotic manipulation and grasping via uncertainty-aware imitation learning—0
Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKACode0
Multi-fidelity Machine Learning for Uncertainty Quantification and Optimization—0
Legitimate ground-truth-free metrics for deep uncertainty classification scoring—0
Full-waveform earthquake source inversion using simulation-based inferenceCode0
Improving Uncertainty Quantification in Large Language Models via Semantic Embeddings—0
Uncertainty quantification for fast reconstruction methods using augmented equivariant bootstrap: Application to radio interferometry—0
Uncertainty Quantification via Hölder Divergence for Multi-View Representation Learning—0
CODES: Benchmarking Coupled ODE SurrogatesCode0
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in learning nonlocal operators—0
Integrating uncertainty quantification into randomized smoothing based robustness guarantees—0
CGKN: A Deep Learning Framework for Modeling Complex Dynamical Systems and Efficient Data AssimilationCode0
GeoFUSE: A High-Efficiency Surrogate Model for Seawater Intrusion Prediction and Uncertainty Reduction—0
Conformal Prediction for Multimodal RegressionCode0
Uncertainty-Error correlations in Evidential Deep Learning models for biomedical segmentation—0
Neural Network Prediction of Strong Lensing Systems with Domain Adaptation and Uncertainty QuantificationCode0
The Probabilistic Tsetlin Machine: A Novel Approach to Uncertainty Quantification—0
Can Uncertainty Quantification Enable Better Learning-based Index Tuning?Code0
Bayes without Underfitting: Fully Correlated Deep Learning Posteriors via Alternating Projections—0
High-Fidelity Transfer of Functional Priors for Wide Bayesian Neural Networks by Learning ActivationsCode0
Ablation Studies for Novel Treatment Effect Estimation Models—0
Building Conformal Prediction Intervals with Approximate Message PassingCode0
Learning signals defined on graphs with optimal transport and Gaussian process regression—0
Bayesian Concept Bottleneck Models with LLM PriorsCode0
Semiparametric Bayesian Inference for a Conditional Moment Equality Model—0
Conditional Uncertainty Quantification for Tensorized Topological Neural Networks—0
Conditional Prediction ROC Bands for Graph ClassificationCode0
A Hybrid Feature Fusion Deep Learning Framework for Leukemia Cancer Detection in Microscopic Blood Sample Using Gated Recurrent Unit and Uncertainty Quantification—0
A Statistical Machine Learning Approach for Adapting Reduced-Order Models using Projected Gaussian Process—0
MultiOrg: A Multi-rater Organoid-detection Dataset—0
Personalizing Low-Rank Bayesian Neural Networks Via Federated Learning—0
Debiasing Mini-Batch Quadratics for Applications in Deep Learning—0
Spectral Representations for Accurate Causal Uncertainty Quantification with Gaussian ProcessesCode0
Generative Conformal Prediction with Vectorized Non-Conformity Scores—0
Supervised Kernel ThinningCode0
Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation—0
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