variational inference

Implicit Causal Models for Genome-wide Association Studies ICLR 2018 Implicit Reparameterization Gradients NeurIPS 2018 Importance Weighting and Variational Inference NeurIPS 2018 Improving Explorability in Variational Inference with Annealed Variational Objectives NeurIPS 2018 Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo NeurIPS 2018 Inference via Low-Dimensional Couplings JMLR 2018 Infinite-Horizon Gaussian Processes NeurIPS 2018 Interpretable Latent Spaces for Learning from Demonstration CoRL 2018 Kernel Implicit Variational Inference ICLR 2018 Large-Scale Cox Process Inference using Variational Fourier Features ICML 2018 Learning an Embedding Space for Transferable Robot Skills ICLR 2018 Learning Attractor Dynamics for Generative Memory NeurIPS 2018 Learning Invariances using the Marginal Likelihood NeurIPS 2018 Learning Priors for Invariance AISTATS 2018 Learning Sparse Latent Representations with the Deep Copula Information Bottleneck ICLR 2018 Learning to Decompose and Disentangle Representations for Video Prediction NeurIPS 2018 Learning to Round for Discrete Labeling Problems AISTATS 2018 Markov Modulated Gaussian Cox Processes for Semi-Stationary Intensity Modeling of Events Data ICML 2018 Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues NeurIPS 2018 Mining Multimodal Repositories for Speech Affecting Diseases Interspeech 2018 Mutual Information Neural Estimation ICML 2018 NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing ACL 2018 Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models AISTATS 2018 Neural Models for Documents with Metadata ACL 2018 Noisy Natural Gradient as Variational Inference ICML 2018