| A Variational Edge Partition Model for Supervised Graph Representation Learning | Feb 7, 2022 | ClassificationGraph Representation Learning | CodeCode Available | 0 | 5 |
| Curve Fitting from Probabilistic Emissions and Applications to Dynamic Item Response Theory | Sep 9, 2019 | Variational Inference | CodeCode Available | 0 | 5 |
| Learning to infer in recurrent biological networks | Jun 18, 2020 | Bayesian InferenceVariational Inference | CodeCode Available | 0 | 5 |
| Generating Neural Networks with Neural Networks | Jan 6, 2018 | DiversityVariational Inference | CodeCode Available | 0 | 5 |
| Benchmarking and optimizing organism wide single-cell RNA alignment methods | Mar 26, 2025 | BenchmarkingDecoder | CodeCode Available | 0 | 5 |
| β-Cores: Robust Large-Scale Bayesian Data Summarization in the Presence of Outliers | Aug 31, 2020 | Bayesian InferenceData Summarization | CodeCode Available | 0 | 5 |
| Approximation Based Variance Reduction for Reparameterization Gradients | Jul 29, 2020 | Variational Inference | CodeCode Available | 0 | 5 |
| Adaptive Path-Integral Autoencoder: Representation Learning and Planning for Dynamical Systems | Jul 5, 2018 | Representation LearningVariational Inference | CodeCode Available | 0 | 5 |
| DAPPER: Scaling Dynamic Author Persona Topic Model to Billion Word Corpora | Nov 3, 2018 | Variational Inference | CodeCode Available | 0 | 5 |
| A Variational Time Series Feature Extractor for Action Prediction | Jul 6, 2018 | Action RecognitionPrediction | 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 |
| A General Method for Amortizing Variational Filtering | Nov 13, 2018 | Inference OptimizationVariational Inference | CodeCode Available | 0 | 5 |
| Fully Bayesian VIB-DeepSSM | May 9, 2023 | AnatomyUncertainty Quantification | CodeCode Available | 0 | 5 |
| Function Space Particle Optimization for Bayesian Neural Networks | Feb 26, 2019 | Reinforcement LearningVariational Inference | CodeCode Available | 0 | 5 |
| GFlowNets and variational inference | Oct 2, 2022 | DiversityReinforcement Learning (RL) | 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 |
| Efficient Training of Probabilistic Neural Networks for Survival Analysis | Apr 9, 2024 | Bayesian InferenceComputational Efficiency | CodeCode Available | 0 | 5 |
| Flexible Tails for Normalizing Flows | Jun 22, 2024 | Density EstimationVariational Inference | CodeCode Available | 0 | 5 |
| Approximate Variational Inference Based on a Finite Sample of Gaussian Latent Variables | Jun 11, 2019 | Bayesian InferenceVariational Inference | CodeCode Available | 0 | 5 |
| Free-Form Variational Inference for Gaussian Process State-Space Models | Feb 20, 2023 | FormState Space Models | CodeCode Available | 0 | 5 |
| Bayesian Semi-supervised Learning with Graph Gaussian Processes | Sep 12, 2018 | Active LearningGaussian Processes | CodeCode Available | 0 | 5 |
| Adaptive Robust Learning using Latent Bernoulli Variables | Dec 1, 2023 | Variational Inference | CodeCode Available | 0 | 5 |
| Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning | Dec 5, 2024 | Computational EfficiencyDeep Learning | CodeCode Available | 0 | 5 |
| Approximate Message Passing for Bayesian Neural Networks | Jan 26, 2025 | Uncertainty QuantificationVariational Inference | CodeCode Available | 0 | 5 |
| Finding the Perfect Fit: Applying Regression Models to ClimateBench v1.0 | Aug 23, 2023 | Benchmarkingregression | CodeCode Available | 0 | 5 |
| Flexible Amortized Variational Inference in qBOLD MRI | Mar 11, 2022 | Bayesian InferenceUncertainty Quantification | CodeCode Available | 0 | 5 |
| From Patches to Images: A Nonparametric Generative Model | Aug 1, 2017 | DenoisingImage Inpainting | CodeCode Available | 0 | 5 |
| Approximate Inference for Stochastic Planning in Factored Spaces | Mar 23, 2022 | Variational Inference | CodeCode Available | 0 | 5 |
| Few-shot Generation of Personalized Neural Surrogates for Cardiac Simulation via Bayesian Meta-Learning | Oct 6, 2022 | Meta-LearningVariational Inference | CodeCode Available | 0 | 5 |
| A Fully Natural Gradient Scheme for Improving Inference of the Heterogeneous Multi-Output Gaussian Process Model | Nov 22, 2019 | Gaussian ProcessesVariational Inference | CodeCode Available | 0 | 5 |
| Bayesian posterior approximation with stochastic ensembles | Dec 15, 2022 | Bayesian Inferenceimage-classification | CodeCode Available | 0 | 5 |
| Accelerating Convergence in Bayesian Few-Shot Classification | May 2, 2024 | ClassificationFew-Shot Learning | CodeCode Available | 0 | 5 |
| Fast post-process Bayesian inference with Variational Sparse Bayesian Quadrature | Mar 9, 2023 | Active LearningBayesian Inference | CodeCode Available | 0 | 5 |
| Approximate Inference for Fully Bayesian Gaussian Process Regression | Dec 31, 2019 | GPRregression | CodeCode Available | 0 | 5 |
| Addressing Catastrophic Forgetting in Few-Shot Problems | Apr 30, 2020 | ClassificationGeneral Classification | CodeCode Available | 0 | 5 |
| Approximate Inference for Constructing Astronomical Catalogs from Images | Feb 28, 2018 | CPUVariational Inference | CodeCode Available | 0 | 5 |
| Fast yet Simple Natural-Gradient Descent for Variational Inference in Complex Models | Jul 12, 2018 | Bayesian InferenceVariational Inference | CodeCode Available | 0 | 5 |
| Finding Convincing Arguments Using Scalable Bayesian Preference Learning | Jun 6, 2018 | Active LearningVariational Inference | CodeCode Available | 0 | 5 |
| Globally Convergent Variational Inference | Jan 14, 2025 | Variational Inference | CodeCode Available | 0 | 5 |
| Learning Deep Generative Models with Annealed Importance Sampling | Jun 12, 2019 | Variational Inference | CodeCode Available | 0 | 5 |
| Factorized Fusion Shrinkage for Dynamic Relational Data | Sep 30, 2022 | Variational Inference | CodeCode Available | 0 | 5 |
| Bayesian Nonparametrics for Offline Skill Discovery | Feb 9, 2022 | Imitation Learningreinforcement-learning | CodeCode Available | 0 | 5 |
| A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification | Jan 2, 2019 | General Classificationimage-classification | CodeCode Available | 0 | 5 |
| Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling | May 19, 2017 | Variational Inference | CodeCode Available | 0 | 5 |
| Exchangeable modelling of relational data: checking sparsity, train-test splitting, and sparse exchangeable Poisson matrix factorization | Dec 6, 2017 | Variational Inference | CodeCode Available | 0 | 5 |
| Manifold Gaussian Variational Bayes on the Precision Matrix | Oct 26, 2022 | Variational Inference | CodeCode Available | 0 | 5 |
| Bayesian Nonlinear Support Vector Machines for Big Data | Jul 18, 2017 | Variational Inference | CodeCode Available | 0 | 5 |
| Estimating treatment effects from single-arm trials via latent-variable modeling | Nov 6, 2023 | Variational Inference | 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 |
