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| Deep Probabilistic Ensembles: Approximate Variational Inference through KL Regularization | Nov 6, 2018 | Active LearningGeneral Classification | —Unverified | 0 |
| Deep Poisson Factorization Machines: factor analysis for mapping behaviors in journalist ecosystem | Dec 18, 2015 | Variational Inference | —Unverified | 0 |
| Deep Operator Networks for Bayesian Parameter Estimation in PDEs | Jan 18, 2025 | parameter estimationPDE Surrogate Modeling | —Unverified | 0 |
| Deep Networks as Denoising Algorithms: Sample-Efficient Learning of Diffusion Models in High-Dimensional Graphical Models | Sep 20, 2023 | DenoisingEfficient Neural Network | —Unverified | 0 |
| Bayesian calibration of differentiable agent-based models | May 24, 2023 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Deep Network Regularization via Bayesian Inference of Synaptic Connectivity | Mar 4, 2018 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Bayesian brains and the Rényi divergence | Jul 12, 2021 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm | May 25, 2018 | SensitivityVariational Inference | —Unverified | 0 |
| Deep Latent Force Models: ODE-based Process Convolutions for Bayesian Deep Learning | Nov 24, 2023 | Time SeriesUncertainty Quantification | —Unverified | 0 |
