| A Sparsity-promoting Dictionary Model for Variational Autoencoders | Mar 29, 2022 | modelVariational Inference | —Unverified | 0 |
| Convolutional Normalizing Flows for Deep Gaussian Processes | Apr 17, 2021 | Gaussian ProcessesVariational Inference | —Unverified | 0 |
| B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data | Mar 13, 2020 | Uncertainty QuantificationVariational Inference | —Unverified | 0 |
| A Sparse and Adaptive Prior for Time-Dependent Model Parameters | Oct 9, 2013 | Variational Inference | —Unverified | 0 |
| Building Bayesian Neural Networks with Blocks: On Structure, Interpretability and Uncertainty | Jun 10, 2018 | Gaussian ProcessesVariational Inference | —Unverified | 0 |
| C^2INet: Realizing Incremental Trajectory Prediction with Prior-Aware Continual Causal Intervention | Nov 19, 2024 | Autonomous DrivingContinual Learning | —Unverified | 0 |
| A Statistically Principled and Computationally Efficient Approach to Speech Enhancement using Variational Autoencoders | May 3, 2019 | Speech EnhancementVariational Inference | —Unverified | 0 |
| Calibration of Model Uncertainty for Dropout Variational Inference | Jun 20, 2020 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| A Latent Variable Model for Two-Dimensional Canonical Correlation Analysis and its Variational Inference | Aug 4, 2017 | Dimensionality ReductionVariational Inference | —Unverified | 0 |
| Boosting Variational Inference With Locally Adaptive Step-Sizes | May 19, 2021 | Variational Inference | —Unverified | 0 |
