variational inference

Bayesian Hierarchical Words Representation Learning ACL 2020 Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances ICML 2020 Bayesian Pseudocoresets NeurIPS 2020 Bayesian Sparsification of Deep C-valued Networks ICML 2020 Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties NeurIPS 2020 Bidirectional Convolutional Poisson Gamma Dynamical Systems NeurIPS 2020 Bi-level Score Matching for Learning Energy-based Latent Variable Models NeurIPS 2020 Black-Box Inference for Non-Linear Latent Force Models AISTATS 2020 Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics ICML 2020 Bridging Maximum Likelihood and Adversarial Learning via α-Divergence AAAI 2020 Capsule Routing via Variational Bayes AAAI 2020 CCA-Flow: Deep Multi-view Subspace Learning with Inverse Autoregressive Flow ACML 2020 Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems ICML 2020 Compositional uncertainty in deep Gaussian processes UAI 2020 Constraining Variational Inference with Geometric Jensen-Shannon Divergence NeurIPS 2020 Continual Learning with Adaptive Weights (CLAW) ICLR 2020 Continual Learning with Bayesian Neural Networks for Non-Stationary Data ICLR 2020 Contrastive Variational Reinforcement Learning for Complex Observations CoRL 2020 Convergence Rates of Variational Inference in Sparse Deep Learning ICML 2020 Convolutional dictionary learning based auto-encoders for natural exponential-family distributions ICML 2020 Correlated Equilibria for Approximate Variational Inference in MRFs PGM 2020 Counterfactual Prediction for Bundle Treatment NeurIPS 2020 Decision-Making with Auto-Encoding Variational Bayes NeurIPS 2020 Deep Archimedean Copulas NeurIPS 2020 Deep Gaussian Markov Random Fields ICML 2020