| Uncertainty Quantification for Fairness in Two-Stage Recommender Systems | May 30, 2022 | FairnessRecommendation Systems | CodeCode Available | 0 | 5 |
| Mining the manifolds of deep generative models for multiple data-consistent solutions of ill-posed tomographic imaging problems | Feb 10, 2022 | Generative Adversarial NetworkStochastic Optimization | CodeCode Available | 0 | 5 |
| Forecasting Local Ionospheric Parameters Using Transformers | Feb 20, 2025 | Uncertainty Quantification | CodeCode Available | 0 | 5 |
| Conditional Prediction ROC Bands for Graph Classification | Oct 20, 2024 | ClassificationDrug Discovery | CodeCode Available | 0 | 5 |
| Modeling Complex Disease Trajectories using Deep Generative Models with Semi-Supervised Latent Processes | Nov 14, 2023 | Time SeriesUncertainty Quantification | CodeCode Available | 0 | 5 |
| Modeling groundwater levels in California's Central Valley by hierarchical Gaussian process and neural network regression | Oct 23, 2023 | Gaussian Processesregression | CodeCode Available | 0 | 5 |
| Moment-based parameter inference with error guarantees for stochastic reaction networks | Jun 25, 2024 | Data IntegrationUncertainty Quantification | CodeCode Available | 0 | 5 |
| Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes | Jun 12, 2019 | Activity RecognitionAudio Classification | CodeCode Available | 0 | 5 |
| Bayesian score calibration for approximate models | Nov 10, 2022 | Bayesian Inferencescoring rule | CodeCode Available | 0 | 5 |
| Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics | May 23, 2023 | Uncertainty Quantification | CodeCode Available | 0 | 5 |
