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Uncertainty Quantification

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TitleStatusHype
Distributional Reinforcement Learning on Path-dependent Options—0
Joint space-time wind field data extrapolation and uncertainty quantification using nonparametric Bayesian dictionary learning—0
A Risk-Aware Adaptive Robust MPC with Learned Uncertainty Quantification—0
Interpretable Bayesian Tensor Network Kernel Machines with Automatic Rank and Feature SelectionCode0
From Physics to Foundation Models: A Review of AI-Driven Quantitative Remote Sensing Inversion—0
Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning—0
UQLM: A Python Package for Uncertainty Quantification in Large Language ModelsCode5
Estimating prevalence with precision and accuracyCode0
NRSeg: Noise-Resilient Learning for BEV Semantic Segmentation via Driving World ModelsCode0
Deterministic Object Pose Confidence Region Estimation—0
Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace InferenceCode0
Forecasting Geopolitical Events with a Sparse Temporal Fusion Transformer and Gaussian Process Hybrid: A Case Study in Middle Eastern and U.S. Conflict Dynamics—0
Uncertainty-Aware Machine-Learning Framework for Predicting Dislocation Plasticity and Stress-Strain Response in FCC Alloys—0
Latent-space Field Tension for Astrophysical Component Detection An application to X-ray imaging—0
Structural System Identification via Validation and Adaptation—0
COIN: Uncertainty-Guarding Selective Question Answering for Foundation Models with Provable Risk Guarantees—0
When Can We Reuse a Calibration Set for Multiple Conformal Predictions?—0
Consensus-Driven Uncertainty for Robotic Grasping based on RGB PerceptionCode0
GNN's Uncertainty Quantification using Self-DistillationCode0
A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers—0
Bayesian Inference for Left-Truncated Log-Logistic Distributions for Time-to-event Data Analysis—0
Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks—0
UProp: Investigating the Uncertainty Propagation of LLMs in Multi-Step Agentic Decision-MakingCode0
Bayesian Joint Model of Multi-Sensor and Failure Event Data for Multi-Mode Failure Prediction—0
Semantic and Feature Guided Uncertainty Quantification of Visual Localization for Autonomous Vehicles—0
Mitigating loss of variance in ensemble data assimilation: machine learning-based and distance-free localizations for better covariance estimation—0
Vine Copulas as Differentiable Computational GraphsCode3
Model-Agnostic, Temperature-Informed Sampling Enhances Cross-Year Crop Mapping with Deep Learning—0
Bridging Data-Driven and Physics-Based Models: A Consensus Multi-Model Kalman Filter for Robust Vehicle State Estimation—0
Beyond Sin-Squared Error: Linear-Time Entrywise Uncertainty Quantification for Streaming PCA—0
Statistical Machine Learning for Astronomy -- A TextbookCode2
Recursive KalmanNet: Deep Learning-Augmented Kalman Filtering for State Estimation with Consistent Uncertainty QuantificationCode1
A Fast, Reliable, and Secure Programming Language for LLM Agents with Code Actions—0
Improving Group Robustness on Spurious Correlation via Evidential AlignmentCode0
Structure and asymptotic preserving deep neural surrogates for uncertainty quantification in multiscale kinetic equations—0
Uncertainty-Masked Bernoulli Diffusion for Camouflaged Object Detection Refinement—0
Uncertainty-Aware Deep Learning for Automated Skin Cancer Classification: A Comprehensive Evaluation—0
Inv-Entropy: A Fully Probabilistic Framework for Uncertainty Quantification in Language ModelsCode1
Bayesian Probabilistic Matrix Factorization—0
Probabilistic Variational Contrastive Learning—0
Textual Bayes: Quantifying Uncertainty in LLM-Based Systems—0
LaDCast: A Latent Diffusion Model for Medium-Range Ensemble Weather ForecastingCode1
Flow Matching Meets PDEs: A Unified Framework for Physics-Constrained Generation—0
Model-Free Kernel Conformal Depth Measures Algorithm for Uncertainty Quantification in Regression Models in Separable Hilbert Spaces—0
End-to-End Probabilistic Framework for Learning with Hard Constraints—0
Graph Neural Networks in Modern AI-aided Drug Discovery—0
Emulating compact binary population synthesis simulations with robust uncertainty quantification and model comparison: Bayesian normalizing flowsCode0
Antithetic Noise in Diffusion Models—0
Testing Hypotheses of Covariate Effects on Topics of DiscourseCode0
Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning—0
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