| Incorporating Word Correlation Knowledge into Topic Modeling | May 1, 2015 | Computational EfficiencyTopic Models | —Unverified | 0 |
| Incremental Variational Inference for Latent Dirichlet Allocation | Jul 17, 2015 | Variational Inference | —Unverified | 0 |
| Independent projections of diffusions: Gradient flows for variational inference and optimal mean field approximations | Sep 23, 2023 | Variational Inference | —Unverified | 0 |
| Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations | Sep 5, 2019 | DisentanglementVariational Inference | —Unverified | 0 |
| Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning | Dec 4, 2019 | Continual LearningVariational Inference | —Unverified | 0 |
| Indian Buffet Process Deep Generative Models for Semi-Supervised Classification | Feb 14, 2014 | ClassificationGeneral Classification | —Unverified | 0 |
| Copula variational inference | Jun 10, 2015 | Stochastic OptimizationVariational Inference | —Unverified | 0 |
| Inducing Interpretable Representations with Variational Autoencoders | Nov 22, 2016 | General ClassificationVariational Inference | —Unverified | 0 |
| Inference for determinantal point processes without spectral knowledge | Jul 4, 2015 | Point ProcessesVariational Inference | —Unverified | 0 |
| Adaptive and Calibrated Ensemble Learning with Dependent Tail-free Process | Dec 8, 2018 | Ensemble LearningModel Selection | —Unverified | 0 |
