Bayesian & Probabilistic

Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE) ICML 2015 End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture NeurIPS 2015 Exact Bayesian Learning of Ancestor Relations in Bayesian Networks AISTATS 2015 Expectation Particle Belief Propagation NeurIPS 2015 Exponential Integration for Hamiltonian Monte Carlo ICML 2015 Face Alignment Using Cascade Gaussian Process Regression Trees CVPR 2015 Falling Rule Lists AISTATS 2015 Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods ICML 2015 Fast Lifted MAP Inference via Partitioning NeurIPS 2015 Fast Second Order Stochastic Backpropagation for Variational Inference 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 Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees NeurIPS 2015 Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning NeurIPS 2015 Gamma Processes, Stick-Breaking, and Variational Inference AISTATS 2015 Gaussian Process Random Fields NeurIPS 2015 GP Kernels for Cross-Spectrum Analysis NeurIPS 2015 Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families NeurIPS 2015 Graphical Models via Univariate Exponential Family Distributions JMLR 2015 Harmonic Exponential Families on Manifolds ICML 2015 HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades ICML 2015 Human Memory Search as Initial-Visit Emitting Random Walk NeurIPS 2015 Image Segmentation in Twenty Questions CVPR 2015 IMU Preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation RSS 2015 Inference for determinantal point processes without spectral knowledge NeurIPS 2015