variational inference

Reimagining Mutual Information for Enhanced Defense against Data Leakage in Collaborative Inference NeurIPS 2024 Removing Biases from Molecular Representations via Information Maximization ICLR 2024 Reparameterization invariance in approximate Bayesian inference NeurIPS 2024 Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks ICML 2024 Reparameterized Variational Rejection Sampling AISTATS 2024 Riemannian Laplace Approximation with the Fisher Metric AISTATS 2024 Risk-sensitive control as inference with Rényi divergence NeurIPS 2024 S$2$AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic ICLR 2024 Safe Abductive Learning in the Presence of Inaccurate Rules AAAI 2024 Sample Average Approximation for Black-Box Variational Inference UAI 2024 Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes NeurIPS 2024 Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits NeurIPS 2024 Self-Supervised Denoising Transformer With Gaussian Process WACV 2024 Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference AISTATS 2024 Sparse Bayesian Deep Learning for Cross Domain Medical Image Reconstruction AAAI 2024 Sparse Bayesian Generative Modeling for Compressive Sensing NeurIPS 2024 Sparse Variational Student-t Processes AAAI 2024 Stein Variational Ergodic Search RSS 2024 Streaming Bayes GFlowNets NeurIPS 2024 Structural Inference with Dynamics Encoding and Partial Correlation Coefficients ICLR 2024 Structured Optimal Variational Inference for Dynamic Latent Space Models JMLR 2024 Structured Probabilistic Coding AAAI 2024 Taming Mode Collapse in Score Distillation for Text-to-3D Generation CVPR 2024 Targeted Separation and Convergence with Kernel Discrepancies JMLR 2024 Text-Guided Variational Image Generation for Industrial Anomaly Detection and Segmentation CVPR 2024