evidence lower bound

Beyond Mean-Field: Tree-Copula Variational Autoencoders for Structured Latent Dependencies UAI 2026 Boundary-Guided Policy Optimization for Memory-efficient RL of Diffusion Large Language Models ACL 2026 COBALT: Censored Optimization and Bayesian Active Learning Techniques UAI 2026 GS^2: Graph-based Spatial Distribution Optimization for Compact 3D Gaussian Splatting CVPR 2026 Implicit Variational Rejection Sampling UAI 2026 VA-p: Variational Policy Alignment for Pixel-Aware Autoregressive Generation CVPR 2026 VBF++: Variational Bayesian Fusion with Context-Aware Priors and Recommendation-Guided Adversarial Refinement for Multimodal Video Recommendation AAAI 2026 Deep Bayesian Filter for Bayes-Faithful Data Assimilation ICML 2025 Deep Incomplete Multi-view Learning via Cyclic Permutation of VAEs ICLR 2025 Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors AAAI 2025 EDMB: Edge Detector with Mamba WACV 2025 ELBOing Stein: Variational Bayes with Stein Mixture Inference ICLR 2025 ELBO, regularized maximum likelihood, and their common one-sample approximation for training stochastic neural networks UAI 2025 New Bounds for Sparse Variational Gaussian Processes ICML 2025 On the Natural Gradient of the Evidence Lower Bound JMLR 2025 Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation ICLR 2025 Unified Discrete Diffusion for Categorical Data JMLR 2025 Variational Learning of Fractional Posteriors ICML 2025 Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing NeurIPS 2024 DiffEnc: Variational Diffusion with a Learned Encoder ICLR 2024 Efficient Mixture Learning in Black-Box Variational Inference ICML 2024 Globally Convergent Variational Inference NeurIPS 2024 Learning Sparse Codes with Entropy-Based ELBOs AISTATS 2024 Logistic Variational Bayes Revisited ICML 2024 Particle Semi-Implicit Variational Inference NeurIPS 2024