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Variational Inference

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TitleStatusHype
Multiple Clustering Views from Multiple Uncertain Experts—0
Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions—0
Multiple scan data association by convex variational inference—0
Multi-Response Heteroscedastic Gaussian Process Models and Their Inference—0
Learning Multiscale Non-stationary Causal Structures—0
Multi-Source Neural Variational Inference—0
Multi-task longitudinal forecasting with missing values on Alzheimer's Disease—0
Multivariate Gaussian Variational Inference by Natural Gradient Descent—0
Multi-View Image Generation from a Single-View—0
Multi-view information fusion using multi-view variational autoencoders to predict proximal femoral strength—0
Multiview Variational Deep Learning with Application to Scalable Indoor Localization—0
Natural Evolution Strategies as a Black Box Estimator for Stochastic Variational Inference—0
Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models—0
Natural Gradient Variational Inference with Gaussian Mixture Models—0
Nearly Dimension-Independent Convergence of Mean-Field Black-Box Variational Inference—0
Nearly Optimal Variational Inference for High Dimensional Regression with Shrinkage Priors—0
Neighborhood Random Walk Graph Sampling for Regularized Bayesian Graph Convolutional Neural Networks—0
NEMR: Network Embedding on Metric of Relation—0
Nested Hierarchical Dirichlet Processes—0
Nested Variational Compression in Deep Gaussian Processes—0
Nested Variational Inference—0
Neural Adaptive Sequential Monte Carlo—0
Neural Dynamic Focused Topic Model—0
Neural Fast Full-Rank Spatial Covariance Analysis for Blind Source Separation—0
Neural information field filter—0
Neural Likelihoods for Multi-Output Gaussian Processes—0
Neural Linear Models with Functional Gaussian Process Priors—0
Neural Mixed Counting Models for Dispersed Topic Discovery—0
Neural Probabilistic Logic Learning for Knowledge Graph Reasoning—0
Neural Relational Inference with Node-Specific Information—0
Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit—0
Neural Structure Learning with Stochastic Differential Equations—0
Neural Topic Model with Reinforcement Learning—0
Neural Variational Dropout Processes—0
Neural Variational Inference and Learning in Undirected Graphical Models—0
Neural Variational Inference and Learning in Belief Networks—0
Neural Variational Inference For Embedding Knowledge Graphs—0
Neuron ranking -- an informed way to condense convolutional neural networks architecture—0
Neuro-Symbolic Entity Alignment via Variational Inference—0
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport—0
Newtonian Monte Carlo: a second-order gradient method for speeding up MCMC—0
Noise-Aware Differentially Private Variational Inference—0
Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization—0
Non-Factorised Variational Inference in Dynamical Systems—0
Nonlinear Hawkes Processes in Time-Varying System—0
Nonlinear Hawkes Process with Gaussian Process Self Effects—0
Nonlinear sparse variational Bayesian learning based model predictive control with application to PEMFC temperature control—0
Nonparametric Automatic Differentiation Variational Inference with Spline Approximation—0
Non-parametric Power-law Data Clustering—0
Nonparametric Variational Auto-encoders for Hierarchical Representation Learning—0
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