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Variational Inference

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TitleStatusHype
Dynamical Variational Autoencoders: A Comprehensive ReviewCode1
Meta-Learning with Shared Amortized Variational InferenceCode0
Training Multimodal Systems for Classification with Multiple Objectives—0
Multiview Variational Deep Learning with Application to Scalable Indoor Localization—0
Deep Variational Network Toward Blind Image RestorationCode1
Improving Fair Predictions Using Variational Inference In Causal ModelsCode0
Variational Inference-Based Dropout in Recurrent Neural Networks for Slot Filling in Spoken Language Understanding—0
Dual Adversarial Auto-Encoders for Clustering—0
Blindness of score-based methods to isolated components and mixing proportions—0
WeLa-VAE: Learning Alternative Disentangled Representations Using Weak Labels—0
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables—0
Instance-Aware Graph Convolutional Network for Multi-Label Classification—0
OCEAN: Online Task Inference for Compositional Tasks with Context AdaptationCode0
Unifying supervised learning and VAEs -- coverage, systematics and goodness-of-fit in normalizing-flow based neural network models for astro-particle reconstructionsCode1
Stochastic Bayesian Neural Networks—0
Uncertainty Quantification using Variational Inference for Biomedical Image SegmentationCode0
ClimAlign: Unsupervised statistical downscaling of climate variables via normalizing flowsCode1
From Rain Generation to Rain RemovalCode1
Investigating maximum likelihood based training of infinite mixtures for uncertainty quantification—0
Dual Gaussian-based Variational Subspace Disentanglement for Visible-Infrared Person Re-IdentificationCode0
Convergence of Sparse Variational Inference in Gaussian Processes RegressionCode1
Approximation Based Variance Reduction for Reparameterization GradientsCode0
Multi-Sample Online Learning for Probabilistic Spiking Neural Networks—0
Complementing Representation Deficiency in Few-shot Image Classification: A Meta-Learning ApproachCode0
Randomized Automatic DifferentiationCode1
Mixture Representation Learning with Coupled Autoencoders—0
GRADE: Graph Dynamic Embedding—0
Measurement error models: from nonparametric methods to deep neural networks—0
State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian ProcessesCode1
VINNAS: Variational Inference-based Neural Network Architecture Search—0
Control as Hybrid Inference—0
Self-Reflective Variational Autoencoder—0
Variational Inference with Continuously-Indexed Normalizing FlowsCode0
Training Restricted Boltzmann Machines with Binary Synapses using the Bayesian Learning Rule—0
Fast Variational Learning in State-Space Gaussian Process ModelsCode1
Meta-Learning Divergences of Variational Inference—0
All in the Exponential Family: Bregman Duality in Thermodynamic Variational InferenceCode0
Neural Mixed Counting Models for Dispersed Topic Discovery—0
Interpretable Operational Risk Classification with Semi-Supervised Variational Autoencoder—0
Learning Sparse Prototypes for Text GenerationCode1
Learning Robot Skills with Temporal Variational Inference—0
Reliable Categorical Variational Inference with Mixture of Discrete Normalizing FlowsCode0
Variational Orthogonal Features—0
On the Relationship Between Active Inference and Control as Inference—0
not-MIWAE: Deep Generative Modelling with Missing not at Random DataCode1
Fast and Flexible Temporal Point Processes with Triangular MapsCode1
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal PosteriorsCode0
Isometric Gaussian Process Latent Variable Model for Dissimilarity Data—0
Calibration of Model Uncertainty for Dropout Variational Inference—0
Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian ProcessesCode1
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