| Testing Visual Attention in Dynamic Environments | Oct 30, 2015 | Variational Inference | —Unverified | 0 | 0 |
| t-Exponential Memory Networks for Question-Answering Machines | Sep 4, 2018 | Language ModelingLanguage Modelling | —Unverified | 0 | 0 |
| Text-Video Retrieval via Variational Multi-Modal Hypergraph Networks | Jan 6, 2024 | RetrievalVariational Inference | —Unverified | 0 | 0 |
| The Block Point Process Model for Continuous-Time Event-Based Dynamic Networks | Nov 29, 2017 | ClusteringStochastic Block Model | —Unverified | 0 | 0 |
| The Deep Latent Position Topic Model for Clustering and Representation of Networks with Textual Edges | Apr 14, 2023 | ClusteringModel Selection | —Unverified | 0 | 0 |
| The Effect of Prior Lipschitz Continuity on the Adversarial Robustness of Bayesian Neural Networks | Jan 7, 2021 | Adversarial RobustnessVariational Inference | —Unverified | 0 | 0 |
| The equivalence between Stein variational gradient descent and black-box variational inference | Apr 4, 2020 | Bayesian InferenceVariational Inference | —Unverified | 0 | 0 |
| The Free Energy Principle for Perception and Action: A Deep Learning Perspective | Jul 13, 2022 | Deep LearningVariational Inference | —Unverified | 0 | 0 |
| The Gaussian Process Latent Autoregressive Model | Nov 23, 2020 | DenoisingGaussian Processes | —Unverified | 0 | 0 |
| The Generalized Reparameterization Gradient | Oct 7, 2016 | Variational Inference | —Unverified | 0 | 0 |
| The Generalized Reparameterization Gradient | Dec 1, 2016 | Variational Inference | —Unverified | 0 | 0 |
| The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks | Feb 7, 2020 | Bayesian InferenceVariational Inference | —Unverified | 0 | 0 |
| Theoretical and Computational Guarantees of Mean Field Variational Inference for Community Detection | Oct 30, 2017 | Bayesian InferenceCommunity Detection | —Unverified | 0 | 0 |
| Theoretical Connection between Locally Linear Embedding, Factor Analysis, and Probabilistic PCA | Mar 25, 2022 | Dimensionality ReductionVariational Inference | —Unverified | 0 | 0 |
| Theoretical guarantees for sampling and inference in generative models with latent diffusions | Mar 5, 2019 | Variational Inference | —Unverified | 0 | 0 |
| The Role of Mutual Information in Variational Classifiers | Oct 22, 2020 | Variational Inference | —Unverified | 0 | 0 |
| The statistical thermodynamics of generative diffusion models: Phase transitions, symmetry breaking and critical instability | Oct 26, 2023 | MemorizationVariational Inference | —Unverified | 0 | 0 |
| The Theory and Algorithm of Ergodic Inference | Nov 17, 2018 | BIG-bench Machine LearningVariational Inference | —Unverified | 0 | 0 |
| The Transitive Information Theory and its Application to Deep Generative Models | Mar 9, 2022 | Inductive BiasVariational Inference | —Unverified | 0 | 0 |
| The Variational Gaussian Process | Nov 20, 2015 | Representation LearningVariational Inference | —Unverified | 0 | 0 |
| The Wyner Variational Autoencoder for Unsupervised Multi-Layer Wireless Fingerprinting | Mar 28, 2023 | Variational Inference | —Unverified | 0 | 0 |
| Thompson sampling for improved exploration in GFlowNets | Jun 30, 2023 | Active LearningDecision Making | —Unverified | 0 | 0 |
| Tightening Bounds for Variational Inference by Revisiting Perturbation Theory | Sep 30, 2019 | Gaussian ProcessesStochastic Optimization | —Unverified | 0 | 0 |
| Tight Variational Bounds via Random Projections and I-Projections | Oct 5, 2015 | Variational Inference | —Unverified | 0 | 0 |
| To Beta or Not To Beta: Information Bottleneck for DigitaL Image Forensics | Aug 11, 2019 | Image ForensicsRepresentation Learning | —Unverified | 0 | 0 |