Variational Inference

Natural image synthesis for the retina with variational information bottleneck representation NeurIPS 2022 Near-Optimal Task Selection for Meta-Learning with Mutual Information and Online Variational Bayesian Unlearning AISTATS 2022 Neural Relational Inference with Node-Specific Information ICLR 2022 Non-Autoregressive Neural Machine Translation with Consistency Regularization Optimized Variational Framework NAACL 2022 One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement NeurIPS 2022 On PAC-Bayesian reconstruction guarantees for VAEs AISTATS 2022 On the detrimental effect of invariances in the likelihood for variational inference NeurIPS 2022 On the relationship between variational inference and auto-associative memory NeurIPS 2022 On the Robustness to Misspecification of α-posteriors and Their Variational Approximations JMLR 2022 Pathfinder: Parallel quasi-Newton variational inference JMLR 2022 Personalized Federated Learning via Variational Bayesian Inference ICML 2022 Personalized Public Policy Analysis in Social Sciences Using Causal-Graphical Normalizing Flows AAAI 2022 Policy Gradients Incorporating the Future ICLR 2022 Posterior Collapse of a Linear Latent Variable Model NeurIPS 2022 Posterior Matching for Arbitrary Conditioning NeurIPS 2022 Rethinking Variational Inference for Probabilistic Programs with Stochastic Support NeurIPS 2022 Revisiting Active Sets for Gaussian Process Decoders NeurIPS 2022 Riemannian Diffusion Models NeurIPS 2022 RL with KL penalties is better viewed as Bayesian inference EMNLP 2022 Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent NeurIPS 2022 Sampling with Mirrored Stein Operators ICLR 2022 Score-Based Diffusion meets Annealed Importance Sampling NeurIPS 2022 Should We Trust This Summary? Bayesian Abstractive Summarization to The Rescue ACL 2022 SIXO: Smoothing Inference with Twisted Objectives NeurIPS 2022 Sliced Wasserstein variational inference ACML 2022