| Rethinking Sharpness-Aware Minimization as Variational Inference | Oct 19, 2022 | Variational Inference | CodeCode Available | 0 |
| Adaptive Robust Learning using Latent Bernoulli Variables | Dec 1, 2023 | Variational Inference | CodeCode Available | 0 |
| Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach | Jul 4, 2022 | Variational Inference | CodeCode Available | 0 |
| Rethinking Variational Inference for Probabilistic Programs with Stochastic Support | Nov 1, 2023 | Variational Inference | CodeCode Available | 0 |
| Loss convergence in a causal Bayesian neural network of retail firm performance | Aug 29, 2020 | Variational Inference | CodeCode Available | 0 |
| Accelerating Convergence in Bayesian Few-Shot Classification | May 2, 2024 | ClassificationFew-Shot Learning | CodeCode Available | 0 |
| Revisiting Active Sets for Gaussian Process Decoders | Sep 10, 2022 | DecoderGaussian Processes | CodeCode Available | 0 |
| Variational Inference with Continuously-Indexed Normalizing Flows | Jul 10, 2020 | Bayesian InferenceDensity Estimation | CodeCode Available | 0 |
| Reward Conditioned Neural Movement Primitives for Population Based Variational Policy Optimization | Nov 9, 2020 | Variational Inference | CodeCode Available | 0 |
| Reweighted Expectation Maximization | Jun 13, 2019 | Bayesian InferenceDensity Estimation | CodeCode Available | 0 |
