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| Wasserstein Generative Learning of Conditional Distribution | Dec 19, 2021 | Density EstimationImage Generation | CodeCode Available | 0 |
| Modeling and inference of spatio-temporal protein dynamics across brain networks | Jan 18, 2019 | Uncertainty QuantificationVariational Inference | CodeCode Available | 0 |
| Modeling Complex Disease Trajectories using Deep Generative Models with Semi-Supervised Latent Processes | Nov 14, 2023 | Time SeriesUncertainty Quantification | CodeCode Available | 0 |
| Modeling groundwater levels in California's Central Valley by hierarchical Gaussian process and neural network regression | Oct 23, 2023 | Gaussian Processesregression | CodeCode Available | 0 |
| Modeling the Dynamics of PDE Systems with Physics-Constrained Deep Auto-Regressive Networks | Jun 13, 2019 | DecoderUncertainty Quantification | CodeCode Available | 0 |
| Uncertainty quantification for predictions of atomistic neural networks | Jul 14, 2022 | Active LearningProperty Prediction | CodeCode Available | 0 |
| Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification | Apr 8, 2023 | Out-of-Distribution Detectionregression | CodeCode Available | 0 |
| Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent | Feb 5, 2018 | Uncertainty Quantification | CodeCode Available | 0 |
