Probabilistic Modeling

Associative Memory via a Sparse Recovery Model NeurIPS 2015 A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding NeurIPS 2015 A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data ICML 2015 Barrier Frank-Wolfe for Marginal Inference NeurIPS 2015 Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM) NeurIPS 2015 Bounding the Cost of Search-Based Lifted Inference NeurIPS 2015 Concave Penalized Estimation of Sparse Gaussian Bayesian Networks JMLR 2015 Consensus Message Passing for Layered Graphical Models AISTATS 2015 Controversy in mechanistic modelling with Gaussian processes ICML 2015 Decomposition Bounds for Marginal MAP NeurIPS 2015 Deep Poisson Factor Modeling NeurIPS 2015 Deep Temporal Sigmoid Belief Networks for Sequence Modeling NeurIPS 2015 Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation NeurIPS 2015 Differentially Private Learning of Structured Discrete Distributions NeurIPS 2015 Discrete Restricted Boltzmann Machines JMLR 2015 Efficient Learning of Continuous-Time Hidden Markov Models for Disease Progression NeurIPS 2015 Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces NeurIPS 2015 Expectation Particle Belief Propagation NeurIPS 2015 Exponential Integration for Hamiltonian Monte Carlo ICML 2015 Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods ICML 2015 Fast Lifted MAP Inference via Partitioning NeurIPS 2015 Finding Galaxies in the Shadows of Quasars with Gaussian Processes ICML 2015 Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial NeurIPS 2015 Gaussian Process Random Fields NeurIPS 2015 GP Kernels for Cross-Spectrum Analysis NeurIPS 2015