| Epistemic Uncertainty Quantification For Pre-Trained Neural Networks | Jan 1, 2024 | Active LearningOut-of-Distribution Detection | —Unverified | 0 | 0 |
| Epistemic Uncertainty Quantification For Pre-trained Neural Network | Apr 15, 2024 | Active LearningOut-of-Distribution Detection | —Unverified | 0 | 0 |
| Epistemic Deep Learning | Jun 15, 2022 | Deep LearningUncertainty Quantification | —Unverified | 0 | 0 |
| Calibrated Physics-Informed Uncertainty Quantification | Feb 6, 2025 | Conformal PredictionUncertainty Quantification | —Unverified | 0 | 0 |
| A recursive Bayesian neural network for constitutive modeling of sands under monotonic loading | Jan 17, 2025 | Bayesian InferenceSand | —Unverified | 0 | 0 |
| A framework for benchmarking uncertainty in deep regression | Sep 10, 2021 | Benchmarkingregression | —Unverified | 0 | 0 |
| Epinet for Content Cold Start | Nov 20, 2024 | Recommendation SystemsThompson Sampling | —Unverified | 0 | 0 |
| Entropy-regularized Gradient Estimators for Approximate Bayesian Inference | Mar 15, 2025 | Bayesian InferenceModel-based Reinforcement Learning | —Unverified | 0 | 0 |
| Entropy-Regularized 2-Wasserstein Distance between Gaussian Measures | Jun 5, 2020 | FormUncertainty Quantification | —Unverified | 0 | 0 |
| Stochasticity in Motion: An Information-Theoretic Approach to Trajectory Prediction | Oct 2, 2024 | Autonomous DrivingDecision Making | —Unverified | 0 | 0 |