| Accelerating Convergence of Stein Variational Gradient Descent via Deep Unfolding | Feb 23, 2024 | Bayesian InferenceVariational Inference | CodeCode Available | 0 |
| A Framework for Variational Inference of Lightweight Bayesian Neural Networks with Heteroscedastic Uncertainties | Feb 22, 2024 | Variational Inference | —Unverified | 0 |
| Bayesian Neural Networks with Domain Knowledge Priors | Feb 20, 2024 | FairnessVariational Inference | —Unverified | 0 |
| Variational Entropy Search for Adjusting Expected Improvement | Feb 17, 2024 | Bayesian OptimizationVariational Inference | —Unverified | 0 |
| Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes | Feb 17, 2024 | Uncertainty QuantificationVariational Inference | —Unverified | 0 |
| Training Bayesian Neural Networks with Sparse Subspace Variational Inference | Feb 16, 2024 | Uncertainty QuantificationVariational Inference | CodeCode Available | 0 |
| MCMC-driven learning | Feb 14, 2024 | Variational Inference | —Unverified | 0 |
| Variational Continual Test-Time Adaptation | Feb 13, 2024 | Test-time AdaptationVariational Inference | —Unverified | 0 |
| Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage? | Feb 9, 2024 | Deep LearningOut-of-Distribution Detection | CodeCode Available | 0 |
| Latent variable model for high-dimensional point process with structured missingness | Feb 8, 2024 | DecoderGaussian Processes | CodeCode Available | 0 |
