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Variational Inference

767 directly classified papers

Papers per year

Papers

Measuring Sample Quality in Algorithms for Intractable Normalizing Function Problems JMLR 2024
A Framework for Improving the Reliability of Black-box Variational Inference JMLR 2024
Symmetric Equilibrium Learning of VAEs AISTATS 2024
Variational Resampling AISTATS 2024
Benefits of Non-Linear Scale Parameterizations in Black Box Variational Inference through Smoothness Results and Gradient Variance Bounds AISTATS 2024
Sample-efficient neural likelihood-free Bayesian inference of implicit HMMs AISTATS 2024
Variational Hybrid-Attention Framework for Multi-Label Few-Shot Aspect Category Detection AAAI 2024
Direct Amortized Likelihood Ratio Estimation AAAI 2024
Inferring stochastic low-rank recurrent neural networks from neural data NIPS 2024
Think Global, Adapt Local: Learning Locally Adaptive K-Nearest Neighbor Kernel Density Estimators AISTATS 2024
Minimax optimal density estimation using a shallow generative model with a one-dimensional latent variable AISTATS 2024
Putting Back the Stops: Integrating Syntax with Neural Topic Models IJCAI 2024
Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing? AISTATS 2024
Optimising Distributions with Natural Gradient Surrogates AISTATS 2024
Variational Gaussian Process Diffusion Processes AISTATS 2024
Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference AISTATS 2024
Towards Generalizable and Interpretable Motion Prediction: A Deep Variational Bayes Approach AISTATS 2024
A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression JMLR 2024
Learning Sparse Codes with Entropy-Based ELBOs AISTATS 2024
Variational Estimators of the Degree-corrected Latent Block Model for Bipartite Networks JMLR 2024
Sparse Variational Student-t Processes AAAI 2024
Wasserstein Proximal Coordinate Gradient Algorithms JMLR 2024
Building Expressive and Tractable Probabilistic Generative Models: A Review IJCAI 2024
Stochastic Approximation with Biased MCMC for Expectation Maximization AISTATS 2024
Riemannian Laplace Approximation with the Fisher Metric AISTATS 2024