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Variational Inference

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TitleStatusHype
Computing with Categories in Machine Learning—0
Gradients should stay on Path: Better Estimators of the Reverse- and Forward KL Divergence for Normalizing Flows—0
AutoBayes: A Compositional Framework for Generalized Variational Inference—0
Gradient Regularisation as Approximate Variational Inference—0
Variational Laplace for Bayesian neural networks—0
Compositional Scene Modeling with Global Object-Centric Representations—0
AUTM Flow: Atomic Unrestricted Time Machine for Monotonic Normalizing Flows—0
Amortized backward variational inference in nonlinear state-space models—0
Gradient-based inference of abstract task representations for generalization in neural networks—0
GRADE: Graph Dynamic Embedding—0
GP-ALPS: Automatic Latent Process Selection for Multi-Output Gaussian Process Models—0
Good Initializations of Variational Bayes for Deep Models—0
Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models—0
A universal probabilistic spike count model reveals ongoing modulation of neural variability—0
Amortised MAP Inference for Image Super-resolution—0
Global Approximate Inference via Local Linearisation for Temporal Gaussian Processes—0
GFlowOut: Dropout with Generative Flow Networks—0
Complementary Information Mutual Learning for Multimodality Medical Image Segmentation—0
Geometric variational inference—0
Geometric Dirichlet Means algorithm for topic inference—0
Comparing the quality of neural network uncertainty estimates for classification problems—0
A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization—0
Generative Video Compression as Hierarchical Variational Inference—0
Generative Temporal Models with Memory—0
Combining Random Walks and Nonparametric Bayesian Topic Model for Community Detection—0
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