variational inference

Few-Shot Non-Parametric Learning with Deep Latent Variable Model NeurIPS 2022 Flow-based Recurrent Belief State Learning for POMDPs ICML 2022 FlowHMM: Flow-based continuous hidden Markov models NeurIPS 2022 Foundation Posteriors for Approximate Probabilistic Inference NeurIPS 2022 Function-space Inference with Sparse Implicit Processes ICML 2022 GATSBI: Generative Adversarial Training for Simulation-Based Inference ICLR 2022 Gaussian Process Boosting JMLR 2022 Gaussian Process Modeling of Approximate Inference Errors for Variational Autoencoders CVPR 2022 Generalised Mutual Information for Discriminative Clustering NeurIPS 2022 Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning NeurIPS 2022 Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning NeurIPS 2022 GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs NeurIPS 2022 Graph Structure Learning with Variational Information Bottleneck AAAI 2022 Grassmann Stein Variational Gradient Descent AISTATS 2022 Hierarchical Phrase-Based Sequence-to-Sequence Learning EMNLP 2022 Hierarchical Variational Memory for Few-shot Learning Across Domains ICLR 2022 Hindsight: Posterior-guided training of retrievers for improved open-ended generation ICLR 2022 How Good Are Low-Rank Approximations in Gaussian Process Regression? AAAI 2022 Importance Weighted Kernel Bayes’ Rule ICML 2022 Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning ICML 2022 Improving Mutual Information Estimation with Annealed and Energy-Based Bounds ICLR 2022 Improving Subgraph Recognition With Variational Graph Information Bottleneck CVPR 2022 Improving Variational Autoencoders with Density Gap-based Regularization NeurIPS 2022 Infinite-Fidelity Coregionalization for Physical Simulation NeurIPS 2022 Information-Theoretic GAN Compression with Variational Energy-based Model NeurIPS 2022