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Variational Inference

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Showing 851–900 of 2274 papers

TitleStatusHype
Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational AutoencodersCode0
Factorized Fusion Shrinkage for Dynamic Relational DataCode0
Correcting the Sub-optimal Bit Allocation—0
Structured Optimal Variational Inference for Dynamic Latent Space Models—0
Compositional Score Modeling for Simulation-based InferenceCode0
Targeted Separation and Convergence with Kernel Discrepancies—0
A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture ModelsCode0
Jensen-Shannon Divergence Based Novel Loss Functions for Bayesian Neural NetworksCode0
Differentially private partitioned variational inferenceCode0
Amortized Variational Inference: A Systematic Review—0
Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification—0
On the detrimental effect of invariances in the likelihood for variational inference—0
Fair Inference for Discrete Latent Variable Models—0
Langevin Autoencoders for Learning Deep Latent Variable ModelsCode0
Modelling Technical and Biological Effects in scRNA-seq data with Scalable GPLVMsCode0
Structured Recognition for Generative Models with Explaining AwayCode0
CARE: Certifiably Robust Learning with Reasoning via Variational InferenceCode0
β-CapsNet: Learning Disentangled Representation for CapsNet by Information Bottleneck—0
Revisiting Active Sets for Gaussian Process DecodersCode0
A Variational Approach to Parameter Estimation for Characterizing 2-D Cluster Variation Method Topographies—0
Bayesian Neural Network Inference via Implicit Models and the Posterior Predictive Distribution—0
ProBoost: a Boosting Method for Probabilistic Classifiers—0
Variational Inference for Model-Free and Model-Based Reinforcement Learning—0
Learning Multiscale Non-stationary Causal Structures—0
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational InferenceCode0
Langevin Diffusion Variational Inference—0
Uncertainty Quantification for Traffic Forecasting: A Unified Approach—0
Fully probabilistic deep models for forward and inverse problems in parametric PDEs—0
Unitary Approximate Message Passing for Matrix Factorization—0
One Simple Trick to Fix Your Bayesian Neural Network—0
Sliced Wasserstein Variational Inference—0
Learning Generalizable Latent Representations for Novel Degradations in Super Resolution—0
Statistical and Computational Trade-offs in Variational Inference: A Case Study in Inferential Model Selection—0
Gradients should stay on Path: Better Estimators of the Reverse- and Forward KL Divergence for Normalizing Flows—0
Mean-field Variational Inference via Wasserstein Gradient Flow—0
The Free Energy Principle for Perception and Action: A Deep Learning Perspective—0
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and UtilityCode0
Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical studyCode0
Challenges and Pitfalls of Bayesian Unlearning—0
Harnessing Out-Of-Distribution Examples via Augmenting Content and StyleCode0
Variational Flow Graphical Model—0
Modeling Randomly Walking Volatility with Chained Gamma Distributions—0
Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approachCode0
Hidden Parameter Recurrent State Space Models For Changing Dynamics ScenariosCode0
Variational Inference for Additive Main and Multiplicative Interaction Effects Models—0
Reconstructing the Universe with Variational self-Boosted Sampling—0
Sum-of-Squares Relaxations for Information Theory and Variational Inference—0
End-to-End Text-to-Speech Based on Latent Representation of Speaking Styles Using Spontaneous Dialogue—0
Modeling Continuous Time Sequences with Intermittent Observations using Marked Temporal Point ProcessesCode0
Cold Posteriors through PAC-Bayes—0
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