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Variational Inference

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TitleStatusHype
Inferring the quantum density matrix with machine learning—0
Infinite Mixture of Inverted Dirichlet Distributions—0
InfoNCE is variational inference in a recognition parameterised model—0
Information Field Theory and Artificial Intelligence—0
Information Theory with Kernel Methods—0
Informative Priors Improve the Reliability of Multimodal Clinical Data Classification—0
Injective flows for star-like manifolds—0
Input Dependent Sparse Gaussian Processes—0
Instance-Aware Graph Convolutional Network for Multi-Label Classification—0
Integrated Non-Factorized Variational Inference—0
Integrating Document Clustering and Topic Modeling—0
Integration of Knowledge Graph Embedding Into Topic Modeling with Hierarchical Dirichlet Process—0
Variational Policy Propagation for Multi-agent Reinforcement Learning—0
Interaction-Aware Topic Model for Microblog Conversations through Network Embedding and User Attention—0
Interactive Graph Convolutional Filtering—0
Interpretable Dynamics Models for Data-Efficient Reinforcement Learning—0
Interpretable Operational Risk Classification with Semi-Supervised Variational Autoencoder—0
Interpretable User Models via Decision-rule Gaussian Processes: Preliminary Results on Energy Storage—0
An Equivalence between Bayesian Priors and Penalties in Variational Inference—0
IntrinsicTimescales.jl: A Julia package to estimate intrinsic (neural) timescales (INTs) from time-series data—0
Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images—0
Introducing Routing Uncertainty in Capsule Networks—0
Investigating maximum likelihood based training of infinite mixtures for uncertainty quantification—0
ISAM-MTL: Cross-subject multi-task learning model with identifiable spikes and associative memory networks—0
ISA-VAE: Independent Subspace Analysis with Variational Autoencoders—0
Is MC Dropout Bayesian?—0
Isometric Gaussian Process Latent Variable Model for Dissimilarity Data—0
Mixture Representation Learning with Coupled Autoencoders—0
Joint Mapping and Calibration via Differentiable Sensor Fusion—0
Joint Modeling of Visual Objects and Relations for Scene Graph Generation—0
Joint Sparse Graph for Enhanced MIMO-AFDM Receiver Design—0
Joint State Estimation and Noise Identification Based on Variational Optimization—0
Kernel Implicit Variational Inference—0
Koopman-Equivariant Gaussian Processes—0
Kullback-Leibler Proximal Variational Inference—0
Langevin Diffusion Variational Inference—0
Langevin Dynamics as Nonparametric Variational Inference—0
Language-guided Skill Learning with Temporal Variational Inference—0
Large Language Bayes—0
Large-scale Heteroscedastic Regression via Gaussian Process—0
Large-Scale Joint Topic, Sentiment & User Preference Analysis for Online Reviews—0
Large Scale Tensor Regression using Kernels and Variational Inference—0
Latent Gaussian process with composite likelihoods and numerical quadrature—0
Latent Matters: Learning Deep State-Space Models—0
Latent mixed-effect models for high-dimensional longitudinal data—0
Latent Time Neural Ordinary Differential Equations—0
Latent Variables on Spheres for Sampling and Inference—0
LAVAE: Disentangling Location and Appearance—0
Law of Large Numbers for Bayesian two-layer Neural Network trained with Variational Inference—0
LazyDINO: Fast, scalable, and efficiently amortized Bayesian inversion via structure-exploiting and surrogate-driven measure transport—0
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