Probabilistic Modeling

Particle Filter Recurrent Neural Networks AAAI 2020 PGM_PyLib: A Toolkit for Probabilistic Graphical Models in Python PGM 2020 Planar Prior Assisted PatchMatch Multi-View Stereo AAAI 2020 Prediction Focused Topic Models via Feature Selection AISTATS 2020 Predictive Uncertainty Estimation for Tractable Deep Probabilistic Models IJCAI 2020 Prior-aware Composition Inference for Spectral Topic Models AISTATS 2020 Probabilistic Assumptions Matter: Improved Models for Distantly-Supervised Document-Level Question Answering ACL 2020 Probabilistic Circuits for Variational Inference in Discrete Graphical Models NeurIPS 2020 Probabilistic Graphical Models with Neural Networks in InferPy PGM 2020 Probabilistic Inference for Predicate Constraint Satisfaction AAAI 2020 Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations NeurIPS 2020 Probabilistic Linear Solvers for Machine Learning NeurIPS 2020 Probabilistic Orientation Estimation with Matrix Fisher Distributions NeurIPS 2020 Probabilistic Regression for Visual Tracking CVPR 2020 Probabilistic Structural Latent Representation for Unsupervised Embedding CVPR 2020 Probabilistic Time Series Forecasting with Shape and Temporal Diversity NeurIPS 2020 Proximity Operator of the Matrix Perspective Function and its Applications NeurIPS 2020 Quantile Graphical Models: a Bayesian Approach JMLR 2020 Regret Bound for Safe Gaussian Process Bandit Optimization L4DC 2020 Residual Neural Processes AAAI 2020 Residual Sum-Product Networks PGM 2020 Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes NeurIPS 2020 Robust Data Programming with Precision-guided Labeling Functions AAAI 2020 Robustness Computation of Dynamic Controllability in Probabilistic Temporal Networks with Ordinary Distributions IJCAI 2020 Sample Complexity of Kalman Filtering for Unknown Systems L4DC 2020