← Bayesian & Probabilistic
Machine Learning › Bayesian & Probabilistic ›

Variational Inference

767 directly classified papers

Papers per year

Papers

Benefits of Non-Linear Scale Parameterizations in Black Box Variational Inference through Smoothness Results and Gradient Variance Bounds AISTATS 2024
Efficient Variational Sequential Information Control AISTATS 2024
Adaptive importance sampling for heavy-tailed distributions via $α$-divergence minimization AISTATS 2024
Generalized Variational Inference via Optimal Transport AAAI 2024
The Evidence Contraction Issue in Deep Evidential Regression: Discussion and Solution AAAI 2024
On Divergence Measures for Training GFlowNets NIPS 2024
On the Quantification of Image Reconstruction Uncertainty Without Training Data WACV 2024
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference NIPS 2024
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction NIPS 2024
Variational Boosted Soft Trees AISTATS 2023
Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification AISTATS 2023
Actually Sparse Variational Gaussian Processes AISTATS 2023
Factorial SDE for Multi-Output Gaussian Process Regression AISTATS 2023
Particle algorithms for maximum likelihood training of latent variable models AISTATS 2023
Multi-Stream Extension of Variational Bayesian HMM Clustering (MS-VBx) for Combined End-to-End and Vector Clustering-based Diarization INTERSPEECH 2023
Beyond Contrastive Learning: A Variational Generative Model for Multilingual Retrieval ACL 2023
Efficient Latent Variable Modeling for Knowledge-Grounded Dialogue Generation EMNLP 2023
Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition AISTATS 2023
Semi-Supervised Deep Regression with Uncertainty Consistency and Variational Model Ensembling via Bayesian Neural Networks AAAI 2023
Diffusion Bridge Mixture Transports, Schrödinger Bridge Problems and Generative Modeling JMLR 2023
The Bayesian Learning Rule JMLR 2023
RevUp: Revise and Update Information Bottleneck for Event Representation EACL 2023
On the geometry of Stein variational gradient descent JMLR 2023
Approximate Stein Classes for Truncated Density Estimation ICML 2023
Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes ICML 2023