| Dirichlet Pruning for Neural Network Compression | Nov 10, 2020 | Neural Network CompressionVariational Inference | CodeCode Available | 0 | 5 |
| Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning | Jun 6, 2024 | reinforcement-learningReinforcement Learning | CodeCode Available | 0 | 5 |
| Fully Bayesian VIB-DeepSSM | May 9, 2023 | AnatomyUncertainty Quantification | CodeCode Available | 0 | 5 |
| Gradient-based optimization for variational empirical Bayes multiple regression | Nov 21, 2024 | regressionVariational Inference | CodeCode Available | 0 | 5 |
| Functional Gradient Flows for Constrained Sampling | Oct 30, 2024 | Variational Inference | CodeCode Available | 0 | 5 |
| Graphite: Iterative Generative Modeling of Graphs | Mar 28, 2018 | Density EstimationGeneral Classification | CodeCode Available | 0 | 5 |
| Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning | Dec 5, 2024 | Computational EfficiencyDeep Learning | CodeCode Available | 0 | 5 |
| Bayesian Inference Forgetting | Jan 16, 2021 | Bayesian InferenceVariational Inference | CodeCode Available | 0 | 5 |
| Flexible Amortized Variational Inference in qBOLD MRI | Mar 11, 2022 | Bayesian InferenceUncertainty Quantification | CodeCode Available | 0 | 5 |
| Discretely Relaxing Continuous Variables for tractable Variational Inference | Dec 1, 2018 | Variational Inference | CodeCode Available | 0 | 5 |
| Bayesian Neural Networks for Virtual Flow Metering: An Empirical Study | Feb 2, 2021 | Bayesian InferenceVariational Inference | CodeCode Available | 0 | 5 |
| Discriminative calibration: Check Bayesian computation from simulations and flexible classifier | May 24, 2023 | Variational Inference | CodeCode Available | 0 | 5 |
| Design of Communication Systems using Deep Learning: A Variational Inference Perspective | Apr 18, 2019 | DecoderVariational Inference | CodeCode Available | 0 | 5 |
| Handling the Positive-Definite Constraint in the Bayesian Learning Rule | Feb 24, 2020 | validVariational Inference | CodeCode Available | 0 | 5 |
| Adaptive importance sampling for heavy-tailed distributions via α-divergence minimization | Oct 25, 2023 | Bayesian OptimizationVariational Inference | CodeCode Available | 0 | 5 |
| Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios | Jun 29, 2022 | State Space ModelsTime Series | CodeCode Available | 0 | 5 |
| Dep-L_0: Improving L_0-based Network Sparsification via Dependency Modeling | Jun 30, 2021 | Network PruningVariational Inference | CodeCode Available | 0 | 5 |
| Disentangling Latent Space for VAE by Label Relevant/Irrelevant Dimensions | Dec 22, 2018 | Variational Inference | CodeCode Available | 0 | 5 |
| A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regime | Feb 11, 2019 | Small Data Image ClassificationUncertainty Quantification | CodeCode Available | 0 | 5 |
| Hierarchical Variational Imitation Learning of Control Programs | Dec 29, 2019 | Imitation LearningVariational Inference | CodeCode Available | 0 | 5 |
| Hierarchical Variational Models | Nov 7, 2015 | Computational EfficiencyVariational Inference | CodeCode Available | 0 | 5 |
| Flexible mean field variational inference using mixtures of non-overlapping exponential families | Oct 14, 2020 | Variable SelectionVariational Inference | CodeCode Available | 0 | 5 |
| Finding Convincing Arguments Using Scalable Bayesian Preference Learning | Jun 6, 2018 | Active LearningVariational Inference | CodeCode Available | 0 | 5 |
| Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models | Feb 6, 2014 | Dimensionality ReductionGaussian Processes | CodeCode Available | 0 | 5 |
| A Factor Graph Approach to Automated Design of Bayesian Signal Processing Algorithms | Nov 8, 2018 | Bayesian Inferenceparameter estimation | CodeCode Available | 0 | 5 |
