| Variational Memory Addressing in Generative Models | Sep 21, 2017 | Few-Shot LearningRepresentation Learning | CodeCode Available | 0 |
| Improving Explorability in Variational Inference with Annealed Variational Objectives | Sep 6, 2018 | Variational Inference | CodeCode Available | 0 |
| Improving Fair Predictions Using Variational Inference In Causal Models | Aug 25, 2020 | BIG-bench Machine LearningFairness | CodeCode Available | 0 |
| Black-box Coreset Variational Inference | Nov 4, 2022 | Bayesian InferenceData Summarization | CodeCode Available | 0 |
| Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models | Jun 7, 2023 | Hyperparameter OptimizationVariational Inference | CodeCode Available | 0 |
| Learning Deep Generative Models with Annealed Importance Sampling | Jun 12, 2019 | Variational Inference | CodeCode Available | 0 |
| Debiasing Evidence Approximations: On Importance-weighted Autoencoders and Jackknife Variational Inference | Jan 1, 2018 | Computational EfficiencyVariational Inference | CodeCode Available | 0 |
| Improving model calibration with accuracy versus uncertainty optimization | Dec 14, 2020 | image-classificationImage Classification | CodeCode Available | 0 |
| Uncertainty Quantification using Variational Inference for Biomedical Image Segmentation | Aug 12, 2020 | Decoderimage-classification | CodeCode Available | 0 |
| Variational Gibbs Inference for Statistical Model Estimation from Incomplete Data | Nov 25, 2021 | BIG-bench Machine LearningNormalising Flows | CodeCode Available | 0 |
| Improving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty in Frequency Inputs | Mar 9, 2015 | Variational Inference | CodeCode Available | 0 |
| Predictive Collective Variable Discovery with Deep Bayesian Models | Sep 18, 2018 | Bayesian InferenceVariational Inference | CodeCode Available | 0 |
| Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structure | Nov 22, 2019 | Bayesian InferenceNeural Architecture Search | CodeCode Available | 0 |
| Unconstrained Monotonic Neural Networks | Aug 14, 2019 | Density EstimationVariational Inference | CodeCode Available | 0 |
| Joint control variate for faster black-box variational inference | Oct 13, 2022 | Stochastic OptimizationVariational Inference | CodeCode Available | 0 |
| VI-OOD: A Unified Representation Learning Framework for Textual Out-of-distribution Detection | Apr 9, 2024 | Out-of-Distribution DetectionOut of Distribution (OOD) Detection | CodeCode Available | 0 |
| Bijectors.jl: Flexible transformations for probability distributions | Oct 16, 2019 | Bayesian InferenceVariational Inference | CodeCode Available | 0 |
| BIISQ: Bayesian nonparametric discovery of Isoforms and Individual Specific Quantification | Mar 24, 2017 | DiversityVariational Inference | CodeCode Available | 0 |
| Preventing Model Collapse in Gaussian Process Latent Variable Models | Apr 2, 2024 | Dimensionality ReductionImputation | CodeCode Available | 0 |
| Asymmetric Variational Autoencoders | Nov 20, 2017 | Density EstimationVariational Inference | CodeCode Available | 0 |
| Understanding MCMC Dynamics as Flows on the Wasserstein Space | Feb 1, 2019 | Novel ConceptsVariational Inference | CodeCode Available | 0 |
| Indian Buffet process for model selection in convolved multiple-output Gaussian processes | Mar 22, 2015 | Gaussian ProcessesModel Selection | CodeCode Available | 0 |
| Prior Density Learning in Variational Bayesian Phylogenetic Parameters Inference | Feb 6, 2023 | Variational Inference | CodeCode Available | 0 |
| PRISM: Privacy-preserving Inter-Site MRI Harmonization via Disentangled Representation Learning | Nov 10, 2024 | Contrastive LearningPrivacy Preserving | CodeCode Available | 0 |
| Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo | Jun 14, 2018 | Gaussian ProcessesVariational Inference | CodeCode Available | 0 |
