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variational inference

2069 papers

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VI

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

Neural Markov Random Field for Stereo Matching CVPR 2024
Structured Optimal Variational Inference for Dynamic Latent Space Models JMLR 2024
Targeted Separation and Convergence with Kernel Discrepancies JMLR 2024
Nonparametric Automatic Differentiation Variational Inference with Spline Approximation AISTATS 2024
Optimising Distributions with Natural Gradient Surrogates AISTATS 2024
Period Singer: Integrating Periodic and Aperiodic Variational Autoencoders for Natural-Sounding End-to-End Singing Voice Synthesis INTERSPEECH 2024
Benefits of Non-Linear Scale Parameterizations in Black Box Variational Inference through Smoothness Results and Gradient Variance Bounds AISTATS 2024
VSGT: Variational Spatial and Gaussian Temporal Graph Models for EEG-based Emotion Recognition IJCAI 2024
On the Quantification of Image Reconstruction Uncertainty Without Training Data WACV 2024
Generative Calibration of Inaccurate Annotation for Label Distribution Learning AAAI 2024
Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing? AISTATS 2024
Probabilistic Integral Circuits AISTATS 2024
Reparameterized Variational Rejection Sampling AISTATS 2024
Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels AISTATS 2024
POAM: Probabilistic Online Attentive Mapping for Efficient Robotic Information Gathering RSS 2024
Joint control variate for faster black-box variational inference AISTATS 2024
Stein Variational Ergodic Search RSS 2024
Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions NIPS 2024
Variational Multi-scale Representation for Estimating Uncertainty in 3D Gaussian Splatting NIPS 2024
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling NIPS 2024
On Divergence Measures for Training GFlowNets NIPS 2024
Bayesian Adaptive Calibration and Optimal Design NIPS 2024
Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space COLT 2024
Variational Estimators of the Degree-corrected Latent Block Model for Bipartite Networks JMLR 2024
Diffusion-NAT: Self-Prompting Discrete Diffusion for Non-Autoregressive Text Generation EACL 2024