Probabilistic Modeling

DMC: A Distributed Model Counter IJCAI 2018 Dynamic Network Model from Partial Observations NeurIPS 2018 Efficient Bayesian Inference of Sigmoidal Gaussian Cox Processes JMLR 2018 Efficiently Sampling from Underlying Models RSS 2018 End-to-End Learning for the Deep Multivariate Probit Model ICML 2018 Error Modeling via Asymmetric Laplace Distribution for Deep Neural Network Based Single-Channel Speech Enhancement Interspeech 2018 Exploiting Graph Regularized Multi-dimensional Hawkes Processes for Modeling Events with Spatio-temporal Characteristics IJCAI 2018 Exponentiated Strongly Rayleigh Distributions NeurIPS 2018 FACTS: A Hierarchical Task-based Control Model of Speech Incorporating Sensory Feedback Interspeech 2018 Faithful Inversion of Generative Models for Effective Amortized Inference NeurIPS 2018 Fast Greedy MAP Inference for Determinantal Point Process to Improve Recommendation Diversity NeurIPS 2018 Feature-correlation-aware Gaussian Process Latent Variable Model ACML 2018 Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery Interspeech 2018 Gamma-Poisson Dynamic Matrix Factorization Embedded with Metadata Influence NeurIPS 2018 Gauged Mini-Bucket Elimination for Approximate Inference AISTATS 2018 Gaussian Process Behaviour in Wide Deep Neural Networks ICLR 2018 Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data AISTATS 2018 Generalizing Tree Probability Estimation via Bayesian Networks NeurIPS 2018 GraphBTM: Graph Enhanced Autoencoded Variational Inference for Biterm Topic Model EMNLP 2018 Graphical model inference: Sequential Monte Carlo meets deterministic approximations NeurIPS 2018 Heterogeneous Multi-output Gaussian Process Prediction NeurIPS 2018 Hierarchical Density Order Embeddings ICLR 2018 High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach ICML 2018 HOGWILD!-Gibbs can be PanAccurate NeurIPS 2018 How Deep Are Deep Gaussian Processes? JMLR 2018