| Deep Bayesian Self-Training | Nov 26, 2018 | ClusteringVariational Inference | CodeCode Available | 0 | 5 |
| Gradient-based optimization for variational empirical Bayes multiple regression | Nov 21, 2024 | regressionVariational Inference | CodeCode Available | 0 | 5 |
| Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors | Jul 9, 2021 | Objectobject-detection | CodeCode Available | 0 | 5 |
| Barrier Frank-Wolfe for Marginal Inference | Nov 6, 2015 | Variational Inference | CodeCode Available | 0 | 5 |
| Functional Gradient Flows for Constrained Sampling | Oct 30, 2024 | Variational Inference | CodeCode Available | 0 | 5 |
| GFlowNets and variational inference | Oct 2, 2022 | DiversityReinforcement Learning (RL) | CodeCode Available | 0 | 5 |
| Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India | Dec 13, 2017 | BIG-bench Machine LearningVariational Inference | CodeCode Available | 0 | 5 |
| GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies | Jul 7, 2023 | Variational Inference | CodeCode Available | 0 | 5 |
| Function Space Particle Optimization for Bayesian Neural Networks | Feb 26, 2019 | Reinforcement LearningVariational Inference | CodeCode Available | 0 | 5 |
| Globally Convergent Variational Inference | Jan 14, 2025 | Variational Inference | CodeCode Available | 0 | 5 |
| Generative Adversarial Networks with Decoder-Encoder Output Noise | Jul 11, 2018 | DecoderImage Generation | CodeCode Available | 0 | 5 |
| Towards Autoencoding Variational Inference for Aspect-based Opinion Summary | Feb 7, 2019 | General ClassificationSentiment Analysis | CodeCode Available | 0 | 5 |
| Deconfounding Imitation Learning with Variational Inference | Nov 4, 2022 | Imitation LearningVariational Inference | CodeCode Available | 0 | 5 |
| Analytical Approximation of the ELBO Gradient in the Context of the Clutter Problem | Apr 16, 2024 | Bayesian InferenceVariational Inference | CodeCode Available | 0 | 5 |
| Generating Neural Networks with Neural Networks | Jan 6, 2018 | DiversityVariational Inference | CodeCode Available | 0 | 5 |
| Debiasing Evidence Approximations: On Importance-weighted Autoencoders and Jackknife Variational Inference | Jan 1, 2018 | Computational EfficiencyVariational Inference | CodeCode Available | 0 | 5 |
| Training Bayesian Neural Networks with Sparse Subspace Variational Inference | Feb 16, 2024 | Uncertainty QuantificationVariational Inference | CodeCode Available | 0 | 5 |
| Coherence-Aware Neural Topic Modeling | Sep 7, 2018 | Topic ModelsVariational Inference | CodeCode Available | 0 | 5 |
| Training Robust Graph Neural Networks by Modeling Noise Dependencies | Feb 27, 2025 | Variational Inference | CodeCode Available | 0 | 5 |
| Generalized Variational Inference: Three arguments for deriving new Posteriors | Apr 3, 2019 | Bayesian InferenceGaussian Processes | CodeCode Available | 0 | 5 |
| Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structure | Nov 22, 2019 | Bayesian InferenceNeural Architecture Search | CodeCode Available | 0 | 5 |
| Gaussian Process-Gated Hierarchical Mixtures of Experts | Feb 9, 2023 | Gaussian ProcessesVariational Inference | CodeCode Available | 0 | 5 |
| Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates | Jan 26, 2023 | Bayesian InferenceVariational Inference | CodeCode Available | 0 | 5 |
| Analyses of Multi-collection Corpora via Compound Topic Modeling | Jun 17, 2019 | Topic ModelsVariational Inference | CodeCode Available | 0 | 5 |
| Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning | May 12, 2022 | Gaussian ProcessesUncertainty Quantification | CodeCode Available | 0 | 5 |
