| Asymmetric Variational Autoencoders | Nov 20, 2017 | Density EstimationVariational Inference | CodeCode Available | 0 | 5 |
| Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee | Nov 15, 2020 | Deep LearningUncertainty Quantification | CodeCode Available | 0 | 5 |
| Functional Gradient Flows for Constrained Sampling | Oct 30, 2024 | Variational Inference | CodeCode Available | 0 | 5 |
| Functional Variational Bayesian Neural Networks | Mar 14, 2019 | Bayesian InferenceGaussian Processes | CodeCode Available | 0 | 5 |
| Compiling Stan to Generative Probabilistic Languages and Extension to Deep Probabilistic Programming | Sep 30, 2018 | Probabilistic ProgrammingRepresentation Learning | CodeCode Available | 0 | 5 |
| Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box | Apr 11, 2023 | Probabilistic ProgrammingStochastic Optimization | CodeCode Available | 0 | 5 |
| Black box variational inference for state space models | Nov 23, 2015 | State Space ModelsTime Series | CodeCode Available | 0 | 5 |
| GCD-DDPM: A Generative Change Detection Model Based on Difference-Feature Guided DDPM | Jun 6, 2023 | Change DetectionDenoising | CodeCode Available | 0 | 5 |
| A Theoretically Grounded Application of Dropout in Recurrent Neural Networks | Dec 16, 2015 | Bayesian InferenceDeep Learning | 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 |
| ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks | Jul 30, 2018 | Data AugmentationVariational Inference | CodeCode Available | 0 | 5 |
| Black-box Variational Inference for Stochastic Differential Equations | Feb 9, 2018 | Variational Inference | CodeCode Available | 0 | 5 |
| Jensen-Shannon Divergence Based Novel Loss Functions for Bayesian Neural Networks | Sep 23, 2022 | regressionVariational Inference | CodeCode Available | 0 | 5 |
| Efficient Inference in Multi-task Cox Process Models | May 24, 2018 | Gaussian ProcessesPoint Processes | CodeCode Available | 0 | 5 |
| Efficient Low Rank Gaussian Variational Inference for Neural Networks | Dec 1, 2020 | Variational Inference | CodeCode Available | 0 | 5 |
| Black Box Variational Inference | Dec 31, 2013 | Stochastic OptimizationVariational Inference | CodeCode Available | 0 | 5 |
| Globally Convergent Variational Inference | Jan 14, 2025 | Variational Inference | CodeCode Available | 0 | 5 |
| Black-box Coreset Variational Inference | Nov 4, 2022 | Bayesian InferenceData Summarization | CodeCode Available | 0 | 5 |
| Amortized variational transdimensional inference | Jun 5, 2025 | Bayesian InferenceBayesian Optimization | CodeCode Available | 0 | 5 |
| Efficient Alternating Minimization Solvers for Wyner Multi-View Unsupervised Learning | Mar 28, 2023 | Computational EfficiencyRepresentation Learning | CodeCode Available | 0 | 5 |
| Coherence-Aware Neural Topic Modeling | Sep 7, 2018 | Topic ModelsVariational Inference | CodeCode Available | 0 | 5 |
| Efficient Gradient-Free Variational Inference using Policy Search | Jul 1, 2018 | Efficient ExplorationVariational Inference | CodeCode Available | 0 | 5 |
| Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates | Jan 26, 2023 | Bayesian InferenceVariational Inference | CodeCode Available | 0 | 5 |
| Efficient Mixture Learning in Black-Box Variational Inference | Jun 11, 2024 | Density EstimationVariational Inference | CodeCode Available | 0 | 5 |
| Bijectors.jl: Flexible transformations for probability distributions | Oct 16, 2019 | Bayesian InferenceVariational Inference | CodeCode Available | 0 | 5 |
