| Bayesian Deep Learning for Remaining Useful Life Estimation via Stein Variational Gradient Descent | Feb 2, 2024 | Variational Inference | CodeCode Available | 1 | 5 |
| Blind Equalization and Channel Estimation in Coherent Optical Communications Using Variational Autoencoders | Apr 25, 2022 | Variational Inference | CodeCode Available | 1 | 5 |
| Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs | Dec 16, 2023 | Time SeriesVariational Inference | CodeCode Available | 1 | 5 |
| A Deep Variational Approach to Clustering Survival Data | Jun 10, 2021 | ClusteringDeep Clustering | CodeCode Available | 1 | 5 |
| alpha-Deep Probabilistic Inference (alpha-DPI): efficient uncertainty quantification from exoplanet astrometry to black hole feature extraction | Jan 21, 2022 | Uncertainty QuantificationVariational Inference | CodeCode Available | 1 | 5 |
| Conditional Matrix Flows for Gaussian Graphical Models | Jun 12, 2023 | Model SelectionVariational Inference | CodeCode Available | 1 | 5 |
| Constraining Variational Inference with Geometric Jensen-Shannon Divergence | Jun 18, 2020 | Variational Inference | CodeCode Available | 1 | 5 |
| A Differentiable Point Process with Its Application to Spiking Neural Networks | Jun 2, 2021 | Variational Inference | CodeCode Available | 1 | 5 |
| A Discrete Variational Recurrent Topic Model without the Reparametrization Trick | Oct 22, 2020 | document understandingVariational Inference | CodeCode Available | 1 | 5 |
| Graph Representation Learning via Causal Diffusion for Out-of-Distribution Recommendation | Aug 1, 2024 | Graph Representation LearningRepresentation Learning | CodeCode Available | 1 | 5 |
