Bayesian & Probabilistic

Flexible Modeling of Diversity with Strongly Log-Concave Distributions NeurIPS 2019 Forward Amortized Inference for Likelihood-Free Variational Marginalization AISTATS 2019 From Lab to Internship and Back Again: Learning Autonomous Systems through Creating a Research and Development Ecosystem AAAI 2019 Function-Space Distributions over Kernels NeurIPS 2019 GASC: Genre-Aware Semantic Change for Ancient Greek ACL 2019 Gaussian Processes with Linear Operator Inequality Constraints JMLR 2019 Gaussian Process Latent Variable Alignment Learning AISTATS 2019 Gaussian Process Models of Sound Change in Indo-Aryan Dialectology ACL 2019 Gaussian Process Modulated Cox Processes under Linear Inequality Constraints AISTATS 2019 Generalized Boltzmann Machine with Deep Neural Structure AISTATS 2019 Generalized Maximum Entropy Estimation JMLR 2019 Generalizing Eye Tracking With Bayesian Adversarial Learning CVPR 2019 Generalizing the theory of cooperative inference AISTATS 2019 Generative Question Answering: Learning to Answer the Whole Question ICLR 2019 Generic Inference in Latent Gaussian Process Models JMLR 2019 Gradient-based Adaptive Markov Chain Monte Carlo NeurIPS 2019 Graph Convolutional Gaussian Processes ICML 2019 Graphical-model based estimation and inference for differential privacy ICML 2019 GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series NeurIPS 2019 Harmonizable mixture kernels with variational Fourier features AISTATS 2019 Hierarchical Discrete Distribution Decomposition for Match Density Estimation CVPR 2019 High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes NeurIPS 2019 How to Exploit Structure while Solving Weighted Model Integration Problems UAI 2019 Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model NeurIPS 2019 Identifiability of Generalized Hypergeometric Distribution (GHD) Directed Acyclic Graphical Models AISTATS 2019