| Free-Form Variational Inference for Gaussian Process State-Space Models | Feb 20, 2023 | FormState Space Models | CodeCode Available | 0 | 5 |
| Flexible Tails for Normalizing Flows | Jun 22, 2024 | Density EstimationVariational Inference | CodeCode Available | 0 | 5 |
| From Patches to Images: A Nonparametric Generative Model | Aug 1, 2017 | DenoisingImage Inpainting | CodeCode Available | 0 | 5 |
| Differentiable Random Partition Models | May 26, 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 |
| Finding Convincing Arguments Using Scalable Bayesian Preference Learning | Jun 6, 2018 | Active LearningVariational 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 |
| Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference | Oct 5, 2018 | Stochastic OptimizationVariational Inference | CodeCode Available | 0 | 5 |
| Annealed Stein Variational Gradient Descent for Improved Uncertainty Estimation in Full-Waveform Inversion | Oct 17, 2024 | Bayesian InferenceVariational Inference | CodeCode Available | 0 | 5 |
| Differentiable Annealed Importance Sampling Minimizes The Symmetrized Kullback-Leibler Divergence Between Initial and Target Distribution | May 23, 2024 | Variational Inference | CodeCode Available | 0 | 5 |
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| Flexible mean field variational inference using mixtures of non-overlapping exponential families | Oct 14, 2020 | Variable SelectionVariational Inference | CodeCode Available | 0 | 5 |
| Differentially Private Federated Variational Inference | Nov 24, 2019 | Bayesian InferenceFederated Learning | CodeCode Available | 0 | 5 |
| Differentially Private Normalizing Flows for Density Estimation, Data Synthesis, and Variational Inference with Application to Electronic Health Records | Feb 11, 2023 | Density EstimationPrivacy Preserving | CodeCode Available | 0 | 5 |
| Bayesian Learning for Deep Neural Network Adaptation | Dec 14, 2020 | speech-recognitionSpeech Recognition | 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 |
| Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization | May 23, 2023 | Deep LearningTime Series | CodeCode Available | 0 | 5 |
| Bayesian Inference on Brain-Computer Interfaces via GLASS | Apr 14, 2023 | Bayesian InferenceEEG | CodeCode Available | 0 | 5 |
| Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors | Jan 5, 2024 | DenoisingVariational Inference | CodeCode Available | 0 | 5 |
| Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs | Mar 20, 2024 | Uncertainty Quantificationvalid | CodeCode Available | 0 | 5 |
| Deterministic Variational Inference for Robust Bayesian Neural Networks | Oct 9, 2018 | Variational Inference | CodeCode Available | 0 | 5 |
| Direct loss minimization algorithms for sparse Gaussian processes | Apr 7, 2020 | Computational EfficiencyGaussian Processes | 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 |
