Bayesian Inference

Learning Concave Conditional Likelihood Models for Improved Analysis of Tandem Mass Spectra NeurIPS 2018 Learning Continuous Time Bayesian Networks in Non-stationary Domains IJCAI 2018 Learning Discrete Weights Using the Local Reparameterization Trick ICLR 2018 Learning Distributions of Shape Trajectories From Longitudinal Datasets: A Hierarchical Model on a Manifold of Diffeomorphisms CVPR 2018 Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds NeurIPS 2018 Learning in Integer Latent Variable Models with Nested Automatic Differentiation ICML 2018 Learning Others' Intentional Models in Multi-Agent Settings Using Interactive POMDPs NeurIPS 2018 Learning Priors for Invariance AISTATS 2018 Learning Structural Weight Uncertainty for Sequential Decision-Making AISTATS 2018 Learning unknown ODE models with Gaussian processes ICML 2018 Lifted Filtering via Exchangeable Decomposition IJCAI 2018 Lifted Weighted Mini-Bucket NeurIPS 2018 Lightweight Probabilistic Deep Networks CVPR 2018 Limbic: Author-Based Sentiment Aspect Modeling Regularized with Word Embeddings and Discourse Relations EMNLP 2018 Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design ICML 2018 Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach AISTATS 2018 Maximizing acquisition functions for Bayesian optimization NeurIPS 2018 Maximum a Posteriori Policy Optimisation ICLR 2018 Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues NeurIPS 2018 Mental Sampling in Multimodal Representations NeurIPS 2018 Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory ICML 2018 Minibatch Gibbs Sampling on Large Graphical Models ICML 2018 Minimax Optimal Bayes Mixtures for Memoryless Sources over Large Alphabets ALT 2018 Mirrored Langevin Dynamics NeurIPS 2018 Multiphase MCMC Sampling for Parameter Inference in Nonlinear Ordinary Differential Equations AISTATS 2018