| Incremental Variational Inference for Latent Dirichlet Allocation | Jul 17, 2015 | Variational Inference | —Unverified | 0 | 0 |
| Independent projections of diffusions: Gradient flows for variational inference and optimal mean field approximations | Sep 23, 2023 | Variational Inference | —Unverified | 0 | 0 |
| Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations | Sep 5, 2019 | DisentanglementVariational Inference | —Unverified | 0 | 0 |
| Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning | Dec 4, 2019 | Continual LearningVariational Inference | —Unverified | 0 | 0 |
| Indian Buffet Process Deep Generative Models for Semi-Supervised Classification | Feb 14, 2014 | ClassificationGeneral Classification | —Unverified | 0 | 0 |
| Inducing Interpretable Representations with Variational Autoencoders | Nov 22, 2016 | General ClassificationVariational Inference | —Unverified | 0 | 0 |
| Inference for determinantal point processes without spectral knowledge | Jul 4, 2015 | Point ProcessesVariational Inference | —Unverified | 0 | 0 |
| Inferring the quantum density matrix with machine learning | Apr 11, 2019 | BIG-bench Machine LearningVariational Inference | —Unverified | 0 | 0 |
| Infinite Mixture of Inverted Dirichlet Distributions | Jul 27, 2018 | Variational Inference | —Unverified | 0 | 0 |
| InfoNCE is variational inference in a recognition parameterised model | Jul 6, 2021 | Bayesian InferenceSelf-Supervised Learning | —Unverified | 0 | 0 |
| Information Field Theory and Artificial Intelligence | Dec 19, 2021 | Variational Inference | —Unverified | 0 | 0 |
| Information Theory with Kernel Methods | Feb 17, 2022 | Variational Inference | —Unverified | 0 | 0 |
| Informative Priors Improve the Reliability of Multimodal Clinical Data Classification | Nov 17, 2023 | Time SeriesVariational Inference | —Unverified | 0 | 0 |
| Injective flows for star-like manifolds | Jun 13, 2024 | Density EstimationVariational Inference | —Unverified | 0 | 0 |
| Input Dependent Sparse Gaussian Processes | Jul 15, 2021 | Gaussian ProcessesVariational Inference | —Unverified | 0 | 0 |
| Instance-Aware Graph Convolutional Network for Multi-Label Classification | Aug 19, 2020 | ClassificationGeneral Classification | —Unverified | 0 | 0 |
| Integrated Non-Factorized Variational Inference | Dec 1, 2013 | Variational Inference | —Unverified | 0 | 0 |
| Integrating Document Clustering and Topic Modeling | Sep 26, 2013 | ClusteringTopic Models | —Unverified | 0 | 0 |
| Integration of Knowledge Graph Embedding Into Topic Modeling with Hierarchical Dirichlet Process | Jun 1, 2019 | Document ClassificationGeneral Classification | —Unverified | 0 | 0 |
| Variational Policy Propagation for Multi-agent Reinforcement Learning | Apr 19, 2020 | Multi-agent Reinforcement Learningreinforcement-learning | —Unverified | 0 | 0 |
| Interaction-Aware Topic Model for Microblog Conversations through Network Embedding and User Attention | Aug 1, 2018 | Network EmbeddingRepresentation Learning | —Unverified | 0 | 0 |
| Interactive Graph Convolutional Filtering | Sep 4, 2023 | Collaborative FilteringMeta-Learning | —Unverified | 0 | 0 |
| Interpretable Dynamics Models for Data-Efficient Reinforcement Learning | Jul 10, 2019 | Model-based Reinforcement Learningreinforcement-learning | —Unverified | 0 | 0 |
| Interpretable Operational Risk Classification with Semi-Supervised Variational Autoencoder | Jul 1, 2020 | ClassificationGeneral Classification | —Unverified | 0 | 0 |
| Interpretable User Models via Decision-rule Gaussian Processes: Preliminary Results on Energy Storage | Oct 16, 2019 | Bayesian InferenceGaussian Processes | —Unverified | 0 | 0 |