Probabilistic Modeling

Rotation Invariant Householder Parameterization for Bayesian PCA ICML 2019 Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes NeurIPS 2019 Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models NeurIPS 2019 Scalable Deep Generative Relational Model with High-Order Node Dependence NeurIPS 2019 Scalable High-Order Gaussian Process Regression AISTATS 2019 Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap ICML 2019 Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference NeurIPS 2019 Scalable Thompson Sampling via Optimal Transport AISTATS 2019 Scalable Training of Inference Networks for Gaussian-Process Models ICML 2019 Semi-Supervised Prosody Modeling Using Deep Gaussian Process Latent Variable Model Interspeech 2019 ShieldNets: Defending Against Adversarial Attacks Using Probabilistic Adversarial Robustness CVPR 2019 Single-Model Uncertainties for Deep Learning NeurIPS 2019 Smoothing Structured Decomposable Circuits NeurIPS 2019 Smoothing the Geometry of Probabilistic Box Embeddings ICLR 2019 Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs NeurIPS 2019 Spell Once, Summon Anywhere: A Two-Level Open-Vocabulary Language Model AAAI 2019 Stein Point Markov Chain Monte Carlo ICML 2019 Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels ICCV 2019 Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond NeurIPS 2019 Stratified Evidence Logics IJCAI 2019 Structured Bayesian Networks: From Inference to Learning with Routes AAAI 2019 Structured Variational Inference in Continuous Cox Process Models NeurIPS 2019 Sum-of-Squares Polynomial Flow ICML 2019 Switching Linear Dynamics for Variational Bayes Filtering ICML 2019 Temporal Difference Variational Auto-Encoder ICLR 2019