| 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 |
| Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval | Nov 25, 2020 | Computational EfficiencyImage Retrieval | —Unverified | 0 |
| Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs | Nov 24, 2020 | Out-of-Distribution Detectionreinforcement-learning | —Unverified | 0 |
| Application of Deep Learning-based Interpolation Methods to Nearshore Bathymetry | Nov 19, 2020 | Deep LearningGenerative Adversarial Network | —Unverified | 0 |
| Theory-guided Auto-Encoder for Surrogate Construction and Inverse Modeling | Nov 17, 2020 | DecoderUncertainty Quantification | —Unverified | 0 |
| Fast Uncertainty Quantification for Deep Object Pose Estimation | Nov 16, 2020 | ObjectPose Estimation | —Unverified | 0 |
| Denoising Score-Matching for Uncertainty Quantification in Inverse Problems | Nov 16, 2020 | DenoisingMRI Reconstruction | CodeCode Available | 0 |
| Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee | Nov 15, 2020 | Deep LearningUncertainty Quantification | CodeCode Available | 0 |
