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Variational Inference

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TitleStatusHype
Streaming Variational Inference for Bayesian Nonparametric Mixture Models—0
Streamlined Variational Inference for Linear Mixed Models with Crossed Random Effects—0
Structured Black Box Variational Inference for Latent Time Series Models—0
Structured Exploration via Hierarchical Variational Policy Networks—0
Structured Optimal Variational Inference for Dynamic Latent Space Models—0
Structured Semi-Implicit Variational Inference—0
Structured Stochastic Gradient MCMC: a hybrid VI and MCMC approach—0
Structured Stochastic Variational Inference—0
Structured Variational Inference for Coupled Gaussian Processes—0
Structured Variational Inference in Partially Observable Unstable Gaussian Process State Space Models—0
Structured Variationally Auto-encoded Optimization—0
Structure learning with Temporal Gaussian Mixture for model-based Reinforcement Learning—0
Structure-Sensitive Graph Dictionary Embedding for Graph Classification—0
Submodular Variational Inference for Network Reconstruction—0
Sum-of-Squares Relaxations for Information Theory and Variational Inference—0
Surrogate Likelihoods for Variational Annealed Importance Sampling—0
Structure-preserving Gaussian Process Dynamics—0
Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting—0
Tag-Weighted Topic Model For Large-scale Semi-Structured Documents—0
Taming Continuous Posteriors for Latent Variational Dialogue Policies—0
TAN-NTM: Topic Attention Networks for Neural Topic Modeling—0
Target Detection on Hyperspectral Images Using MCMC and VI Trained Bayesian Neural Networks—0
Targeted Separation and Convergence with Kernel Discrepancies—0
Temporal Positive-unlabeled Learning for Biomedical Hypothesis Generation via Risk Estimation—0
Tensorizing flows: a tool for variational inference—0
Testing Visual Attention in Dynamic Environments—0
t-Exponential Memory Networks for Question-Answering Machines—0
Text-Video Retrieval via Variational Multi-Modal Hypergraph Networks—0
The Block Point Process Model for Continuous-Time Event-Based Dynamic Networks—0
The Deep Latent Position Topic Model for Clustering and Representation of Networks with Textual Edges—0
The Effect of Prior Lipschitz Continuity on the Adversarial Robustness of Bayesian Neural Networks—0
The equivalence between Stein variational gradient descent and black-box variational inference—0
The Free Energy Principle for Perception and Action: A Deep Learning Perspective—0
The Gaussian Process Latent Autoregressive Model—0
The Generalized Reparameterization Gradient—0
The Generalized Reparameterization Gradient—0
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks—0
Theoretical and Computational Guarantees of Mean Field Variational Inference for Community Detection—0
Theoretical Connection between Locally Linear Embedding, Factor Analysis, and Probabilistic PCA—0
Theoretical guarantees for sampling and inference in generative models with latent diffusions—0
The Role of Mutual Information in Variational Classifiers—0
The statistical thermodynamics of generative diffusion models: Phase transitions, symmetry breaking and critical instability—0
The Theory and Algorithm of Ergodic Inference—0
The Transitive Information Theory and its Application to Deep Generative Models—0
The Variational Gaussian Process—0
The Wyner Variational Autoencoder for Unsupervised Multi-Layer Wireless Fingerprinting—0
Thompson sampling for improved exploration in GFlowNets—0
Tightening Bounds for Variational Inference by Revisiting Perturbation Theory—0
Tight Variational Bounds via Random Projections and I-Projections—0
To Beta or Not To Beta: Information Bottleneck for DigitaL Image Forensics—0
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