| Sparse Gaussian Process Variational Autoencoders | Oct 20, 2020 | Computational EfficiencyVariational Inference | CodeCode Available | 0 |
| Functional Variational Bayesian Neural Networks | Mar 14, 2019 | Bayesian InferenceGaussian Processes | CodeCode Available | 0 |
| Optimising Distributions with Natural Gradient Surrogates | Oct 18, 2023 | Variational Inference | CodeCode Available | 0 |
| Function Space Particle Optimization for Bayesian Neural Networks | Feb 26, 2019 | Reinforcement LearningVariational Inference | CodeCode Available | 0 |
| Optimization Proxies using Limited Labeled Data and Training Time -- A Semi-Supervised Bayesian Neural Network Approach | Oct 4, 2024 | Bayesian InferenceManagement | CodeCode Available | 0 |
| Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach | Oct 26, 2022 | Thompson SamplingVariational Inference | CodeCode Available | 0 |
| CCSL: A Causal Structure Learning Method from Multiple Unknown Environments | Nov 18, 2021 | Causal DiscoveryClustering | CodeCode Available | 0 |
| Orthogonally Decoupled Variational Gaussian Processes | Sep 24, 2018 | Gaussian ProcessesVariational Inference | CodeCode Available | 0 |
| Variational Delayed Policy Optimization | May 23, 2024 | MuJoCoReinforcement Learning (RL) | CodeCode Available | 0 |
| Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models | Jun 13, 2019 | Variational Inference | CodeCode Available | 0 |
| Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference | Jul 24, 2024 | DenoisingGaussian Processes | CodeCode Available | 0 |
| Tree-based variational inference for Poisson log-normal models | Jun 25, 2024 | Knowledge GraphsVariational Inference | CodeCode Available | 0 |
| PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement Learning | Jun 22, 2022 | counterfactualMulti-agent Reinforcement Learning | CodeCode Available | 0 |
| A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models | Sep 23, 2022 | Variational Inference | CodeCode Available | 0 |
| Dep-L_0: Improving L_0-based Network Sparsification via Dependency Modeling | Jun 30, 2021 | Network PruningVariational Inference | CodeCode Available | 0 |
| Deep Variational Implicit Processes | Jun 14, 2022 | Gaussian ProcessesVariational Inference | CodeCode Available | 0 |
| Gaussian Process-Gated Hierarchical Mixtures of Experts | Feb 9, 2023 | Gaussian ProcessesVariational Inference | CodeCode Available | 0 |
| Analyses of Multi-collection Corpora via Compound Topic Modeling | Jun 17, 2019 | Topic ModelsVariational Inference | CodeCode Available | 0 |
| Neural Causal Graph Collaborative Filtering | Jul 10, 2023 | Collaborative FilteringGraph Learning | CodeCode Available | 0 |
| Sparse Variational Inference: Bayesian Coresets from Scratch | Jun 7, 2019 | Variational Inference | CodeCode Available | 0 |
| Parametric Gaussian Process Regression for Big Data | Apr 11, 2017 | Gaussian Processesregression | CodeCode Available | 0 |
| CARE: Certifiably Robust Learning with Reasoning via Variational Inference | Sep 12, 2022 | Variational Inference | CodeCode Available | 0 |
| A Factor Graph Approach to Automated Design of Bayesian Signal Processing Algorithms | Nov 8, 2018 | Bayesian Inferenceparameter estimation | CodeCode Available | 0 |
| A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference | Jan 8, 2019 | Bayesian InferenceGeneral Classification | CodeCode Available | 0 |
| Generalized Variational Inference: Three arguments for deriving new Posteriors | Apr 3, 2019 | Bayesian InferenceGaussian Processes | CodeCode Available | 0 |
