Probabilistic Modeling

Variational Temporal Abstraction NeurIPS 2019 Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs ICLR 2019 Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes NeurIPS 2019 A Bayesian Latent Variable Model of User Preferences with Item Context IJCAI 2018 A Bayesian Nonparametric View on Count-Min Sketch NeurIPS 2018 Accurate Uncertainties for Deep Learning Using Calibrated Regression ICML 2018 A Hidden Absorbing Semi-Markov Model for Informatively Censored Temporal Data: Learning and Inference JMLR 2018 A Lattice Representation of Independence Relations PGM 2018 Algebraic tests of general Gaussian latent tree models NeurIPS 2018 Algorithmic Linearly Constrained Gaussian Processes NeurIPS 2018 AMR Parsing as Graph Prediction with Latent Alignment ACL 2018 Approximate Knowledge Compilation by Online Collapsed Importance Sampling NeurIPS 2018 Approximating the maximum weighted decomposable graph problem with applications to probabilistic graphical models PGM 2018 A Probabilistic Annotation Model for Crowdsourcing Coreference EMNLP 2018 A probabilistic framework for multi-view feature learning with many-to-many associations via neural networks ICML 2018 A probabilistic population code based on neural samples NeurIPS 2018 A Savage-style Utility Theory for Belief Functions IJCAI 2018 A Scalable Laplace Approximation for Neural Networks ICLR 2018 A Spectral Approach to Gradient Estimation for Implicit Distributions ICML 2018 Assessing Quality Estimation Models for Sentence-Level Prediction COLING 2018 Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language NeurIPS 2018 Batch Normalized Deep Boltzmann Machines ACML 2018 Bayesian Alignments of Warped Multi-Output Gaussian Processes NeurIPS 2018 Bayesian Network Structure Learning with Side Constraints PGM 2018 Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling AISTATS 2018