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Variational Inference

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Showing 1051–1100 of 2274 papers

TitleStatusHype
A derivation of variational message passing (VMP) for latent Dirichlet allocation (LDA)—0
Extracting Topics with Simultaneous Word Co-occurrence and Semantic Correlation Graphs: Neural Topic Modeling for Short Texts—0
Diversity and Consistency: Exploring Visual Question-Answer Pair Generation—0
VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media—0
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels—0
TopicNet: Semantic Graph-Guided Topic DiscoveryCode0
Relay Variational Inference: A Method for Accelerated Encoderless VI—0
Uncertainty quantification in non-rigid image registration via stochastic gradient Markov chain Monte CarloCode0
Regularizing Variational Autoencoder with Diversity and Uncertainty AwarenessCode0
Interpolating between sampling and variational inference with infinite stochastic mixturesCode0
VISinger: Variational Inference with Adversarial Learning for End-to-End Singing Voice Synthesis—0
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modelingCode0
Is MC Dropout Bayesian?—0
Pathologies in priors and inference for Bayesian transformers—0
Marginally calibrated response distributions for end-to-end learning in autonomous drivingCode0
Conditional Deep Gaussian Processes: empirical Bayes hyperdata learningCode0
Variational Marginal Particle FiltersCode0
Variational Inference for Discriminative Learning with Generative Modeling of Feature Incompletion—0
iLQR-VAE : control-based learning of input-driven dynamics with applications to neural data—0
How to deal with missing data in supervised deep learning?—0
Function-Space Variational Inference for Deep Bayesian Classification—0
Variational Component Decoder for Source Extraction from Nonlinear Mixture—0
Neural Variational Dropout Processes—0
f-Divergence Thermodynamic Variational Objective: a Deformed Geometry Perspective—0
Learning to Dequantise with Truncated Flows—0
EinSteinVI: General and Integrated Stein Variational Inference—0
Edge Partition Modulated Graph Convolutional Networks—0
Variational Inference for Continuous-Time Switching Dynamical Systems—0
Tractable Dendritic RNNs for Identifying Unknown Nonlinear Dynamical Systems—0
Neural Relational Inference with Node-Specific Information—0
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How—0
A First-Order Method for Estimating Natural Gradients for Variational Inference with Gaussians and Gaussian Mixture Models—0
Learning From Unpaired Data: A Variational Bayes Approach—0
Deep Ensemble as a Gaussian Process Posterior—0
Variational Inference via Resolution of Singularities—0
Deep Attentive Variational Inference—0
UNCERTAINTY QUANTIFICATION USING VARIATIONAL INFERENCE FOR BIOMEDICAL IMAGE SEGMENTATION—0
Sparse Gaussian Processes for Stochastic Differential Equations—0
Using Soft Labels to Model Uncertainty in Medical Image Segmentation—0
Scalable Multi-Task Gaussian Processes with Neural Embedding of Coregionalization—0
Variational Disentanglement for Domain Generalization—0
Stochastic Neural Radiance Fields: Quantifying Uncertainty in Implicit 3D Representations—0
A Mathematical Walkthrough and Discussion of the Free Energy Principle—0
An Introduction to Variational Inference—0
Variational Inference with NoFAS: Normalizing Flow with Adaptive Surrogate for Computationally Expensive ModelsCode0
Modeling Item Response Theory with Stochastic Variational Inference—0
Few Shot Activity Recognition Using Variational Inference—0
Variational Inference at Glacier Scale—0
Regularized Sequential Latent Variable Models with Adversarial Neural Networks—0
A variational Bayesian spatial interaction model for estimating revenue and demand at business facilities—0
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