variational inference

2069 papers

Explore in graph

Also known as

VI-NET VRNN VBI SVI VIBE VQ-VAE ADVI VARNET MCVI PARVI SAVI VI VAE VMP VB BBVI ELBO VIB

Co-occurring keywords

bayesian inference (1904) gaussian process (1198) generative model (2889) variational autoencoder (1282) latent variable model (564) probabilistic modeling (851) representation learning (6174) uncertainty quantification (1365) latent variable (541) approximate inference (253)

Papers

Optimal Classification under Performative Distribution Shift NIPS 2024

Variational Estimators of the Degree-corrected Latent Block Model for Bipartite Networks JMLR 2024

Unscrambling disease progression at scale: fast inference of event permutations with optimal transport NIPS 2024

Parametric model reduction of mean-field and stochastic systems via higher-order action matching NIPS 2024

Probabilistic Integral Circuits AISTATS 2024

A versatile informative diffusion model for single-cell ATAC-seq data generation and analysis NIPS 2024

eXponential FAmily Dynamical Systems (XFADS): Large-scale nonlinear Gaussian state-space modeling NIPS 2024

Identifiable Feature Learning for Spatial Data with Nonlinear ICA AISTATS 2024

Learning Sparse Codes with Entropy-Based ELBOs AISTATS 2024

Sparse Bayesian Generative Modeling for Compressive Sensing NIPS 2024

On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models NIPS 2024

Wasserstein Proximal Coordinate Gradient Algorithms JMLR 2024

Towards Human-Like Machine Comprehension: Few-Shot Relational Learning in Visually-Rich Documents COLING 2024

Sparse Variational Student-t Processes AAAI 2024

Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits NIPS 2024

MixFlows: principled variational inference via mixed flows ICML 2023

CataBEEM: Integrating Latent Interaction Categories in Node-wise Community Detection Models for Network Data ICML 2023

Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes ICML 2023

Neural Markov Jump Processes ICML 2023

Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting ICML 2023

MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks ICML 2023

Euler-Lagrange Analysis of Generative Adversarial Networks JMLR 2023

Cluster-Specific Predictions with Multi-Task Gaussian Processes JMLR 2023

Variational Sparse Inverse Cholesky Approximation for Latent Gaussian Processes via Double Kullback-Leibler Minimization ICML 2023

Learning Noisy OR Bayesian Networks with Max-Product Belief Propagation ICML 2023