| Privacy Preserving Bayesian Federated Learning in Heterogeneous Settings | Jun 13, 2023 | Federated LearningPrivacy Preserving | —Unverified | 0 |
| A Brief Review of Hypernetworks in Deep Learning | Jun 12, 2023 | Causal InferenceContinual Learning | CodeCode Available | 0 |
| Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing | Jun 11, 2023 | Probabilistic Deep Learningregression | CodeCode Available | 0 |
| Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks | Jun 9, 2023 | Uncertainty Quantification | CodeCode Available | 0 |
| Real-time whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations | Jun 8, 2023 | parameter estimationUncertainty Quantification | —Unverified | 0 |
| Conformal Prediction for Federated Uncertainty Quantification Under Label Shift | Jun 8, 2023 | Conformal PredictionFederated Learning | —Unverified | 0 |
| Using Imperfect Surrogates for Downstream Inference: Design-based Supervised Learning for Social Science Applications of Large Language Models | Jun 7, 2023 | Uncertainty Quantificationvalid | —Unverified | 0 |
| Estimating Uncertainty in PET Image Reconstruction via Deep Posterior Sampling | Jun 7, 2023 | Generative Adversarial NetworkImage Reconstruction | —Unverified | 0 |
| Uncertainty in Natural Language Processing: Sources, Quantification, and Applications | Jun 5, 2023 | Uncertainty Quantification | —Unverified | 0 |
| Global universal approximation of functional input maps on weighted spaces | Jun 5, 2023 | Gaussian Processesregression | CodeCode Available | 0 |
| Distributionally robust uncertainty quantification via data-driven stochastic optimal control | Jun 4, 2023 | LEMMAUncertainty Quantification | —Unverified | 0 |
| Deep Operator Learning-based Surrogate Models with Uncertainty Quantification for Optimizing Internal Cooling Channel Rib Profiles | Jun 1, 2023 | Operator learningUncertainty Quantification | —Unverified | 0 |
| A General Framework for Uncertainty Quantification via Neural SDE-RNN | Jun 1, 2023 | ImputationTime Series | —Unverified | 0 |
| A New PHO-rmula for Improved Performance of Semi-Structured Networks | Jun 1, 2023 | Uncertainty Quantificationvalid | —Unverified | 0 |
| Quantifying Deep Learning Model Uncertainty in Conformal Prediction | Jun 1, 2023 | Conformal PredictionDecision Making | —Unverified | 0 |
| Quantifying Representation Reliability in Self-Supervised Learning Models | May 31, 2023 | Self-Supervised LearningUncertainty Quantification | CodeCode Available | 0 |
| Offline Meta Reinforcement Learning with In-Distribution Online Adaptation | May 31, 2023 | Meta Reinforcement Learningreinforcement-learning | CodeCode Available | 0 |
| Perturbation-Assisted Sample Synthesis: A Novel Approach for Uncertainty Quantification | May 30, 2023 | DiversityImage Generation | CodeCode Available | 0 |
| Probabilistic computation and uncertainty quantification with emerging covariance | May 30, 2023 | Uncertainty Quantification | CodeCode Available | 0 |
| Non-convex Bayesian Learning via Stochastic Gradient Markov Chain Monte Carlo | May 30, 2023 | Uncertainty Quantification | —Unverified | 0 |
| Acceleration of stochastic gradient descent with momentum by averaging: finite-sample rates and asymptotic normality | May 28, 2023 | Uncertainty Quantification | —Unverified | 0 |
| USIM-DAL: Uncertainty-aware Statistical Image Modeling-based Dense Active Learning for Super-resolution | May 27, 2023 | Active LearningDepth Estimation | —Unverified | 0 |
| Bayesian Spike Train Inference via Non-Local Priors | May 27, 2023 | Uncertainty Quantification | —Unverified | 0 |
| Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks | May 26, 2023 | Gaussian Processesregression | —Unverified | 0 |
| Better Batch for Deep Probabilistic Time Series Forecasting | May 26, 2023 | Decision MakingProbabilistic Time Series Forecasting | CodeCode Available | 0 |
