Bayesian Inference

Fast Iterative Combinatorial Auctions via Bayesian Learning AAAI 2019 Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes NeurIPS 2019 Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs AAAI 2019 Feed-forward Propagation in Probabilistic Neural Networks with Categorical and Max Layers ICLR 2019 FilterReg: Robust and Efficient Probabilistic Point-Set Registration Using Gaussian Filter and Twist Parameterization CVPR 2019 Finding All Bayesian Network Structures within a Factor of Optimal AAAI 2019 Fisher Efficient Inference of Intractable Models NeurIPS 2019 Forward Amortized Inference for Likelihood-Free Variational Marginalization AISTATS 2019 From Hard to Soft: Understanding Deep Network Nonlinearities via Vector Quantization and Statistical Inference ICLR 2019 Fully Distributed Bayesian Optimization with Stochastic Policies IJCAI 2019 FUNCTIONAL VARIATIONAL BAYESIAN NEURAL NETWORKS ICLR 2019 Function-Space Distributions over Kernels NeurIPS 2019 Function Space Particle Optimization for Bayesian Neural Networks ICLR 2019 GANAK: A Scalable Probabilistic Exact Model Counter IJCAI 2019 GASC: Genre-Aware Semantic Change for Ancient Greek ACL 2019 Gaussian Processes with Linear Operator Inequality Constraints JMLR 2019 Gaussian Process Models of Sound Change in Indo-Aryan Dialectology ACL 2019 Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret COLT 2019 Gaussian Regression with Convex Constraints AISTATS 2019 Generalized Approximate Survey Propagation for High-Dimensional Estimation ICML 2019 Generating and Sampling Orbits for Lifted Probabilistic Inference UAI 2019 Generic Inference in Latent Gaussian Process Models JMLR 2019 GOODE: A Gaussian Off-The-Shelf Ordinary Differential Equation Solver ICML 2019 Good Initializations of Variational Bayes for Deep Models ICML 2019 Gradient-based Adaptive Markov Chain Monte Carlo NeurIPS 2019