Learning Graphical Models
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with $\beta$-Divergences
Jeremias Knoblauch, Jack E. Jewson, Theodoros Damoulas
Neural Information Processing Systems http://nips.cc/
Predictive Approximate Bayesian Computation via Saddle Points
Yingxiang Yang, Bo Dai, Negar Kiyavash, Niao He
Neural Information Processing Systems http://nips.cc/
Computationally and statistically efficient learning of causal Bayes nets using path queries
Neural Information Processing Systems http://nips.cc/
Learning low-dimensional state embeddings and metastable clusters from time series data
Yifan Sun, Yaqi Duan, Hao Gong, Mengdi Wang
Neural Information Processing Systems http://nips.cc/
Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms
Shahana Ibrahim, Xiao Fu, Nikolaos Kargas, Kejun Huang
Neural Information Processing Systems http://nips.cc/
Modeling Dynamic Functional Connectivity with Latent Factor Gaussian Processes
Lingge Li, Dustin Pluta, Babak Shahbaba, Norbert Fortin, Hernando Ombao, Pierre Baldi
Neural Information Processing Systems http://nips.cc/
Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language
Neural Information Processing Systems http://nips.cc/
Data-dependent PAC-Bayes priors via differential privacy
Gintare Karolina Dziugaite, Daniel M. Roy
Neural Information Processing Systems http://nips.cc/
Integrating Bayesian and Discriminative Sparse Kernel Machines for Multi-class Active Learning
Neural Information Processing Systems http://nips.cc/
MinimumSteinDiscrepancyEstimators
Examples of such models arise naturally in modelling images [27, 39], natural language [54], Markov random fields [61] and nonparametric density estimation [63, 69].