| Active Learning for Deep Gaussian Process Surrogates | Dec 15, 2020 | Active LearningGaussian Processes | CodeCode Available | 0 |
| Probabilistic Contrastive Principal Component Analysis | Dec 14, 2020 | Dimensionality ReductionUncertainty Quantification | CodeCode Available | 1 |
| NP-ODE: Neural Process Aided Ordinary Differential Equations for Uncertainty Quantification of Finite Element Analysis | Dec 12, 2020 | Uncertainty Quantification | CodeCode Available | 0 |
| Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification | Dec 4, 2020 | Bayesian InferenceDecision Making Under Uncertainty | CodeCode Available | 1 |
| Asymptotic normality and confidence intervals for derivatives of 2-layers neural network in the random features model | Dec 1, 2020 | regressionUncertainty Quantification | —Unverified | 0 |
| Non-reversible Gaussian processes for identifying latent dynamical structure in neural data | Dec 1, 2020 | Gaussian ProcessesModel Selection | —Unverified | 0 |
| Derivative-Informed Projected Neural Networks for High-Dimensional Parametric Maps Governed by PDEs | Nov 30, 2020 | Experimental DesignUncertainty Quantification | —Unverified | 0 |
| A Backward SDE Method for Uncertainty Quantification in Deep Learning | Nov 28, 2020 | BIG-bench Machine LearningDeep Learning | —Unverified | 0 |
| Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules | Nov 28, 2020 | Drug DiscoveryUncertainty Quantification | CodeCode Available | 1 |
| Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval | Nov 25, 2020 | Computational EfficiencyImage Retrieval | —Unverified | 0 |
