Bayesian & Probabilistic

SMIL: Multimodal Learning with Severely Missing Modality AAAI 2021 Solving Inverse Problems with a Flow-based Noise Model ICML 2021 Sparse encoding for more-interpretable feature-selecting representations in probabilistic matrix factorization ICLR 2021 Sparse Popularity Adjusted Stochastic Block Model JMLR 2021 Sparse Uncertainty Representation in Deep Learning with Inducing Weights NeurIPS 2021 Sparse within Sparse Gaussian Processes using Neighbor Information ICML 2021 Spatio-Temporal Variational Gaussian Processes NeurIPS 2021 Speaker Diarization Using Two-Pass Leave-One-Out Gaussian PLDA Clustering of DNN Embeddings Interspeech 2021 Spherical Confidence Learning for Face Recognition CVPR 2021 State-Based Recurrent SPMNs for Decision-Theoretic Planning under Partial Observability IJCAI 2021 StatEcoNet: Statistical Ecology Neural Networks for Species Distribution Modeling AAAI 2021 Stochastic block model entropy and broadcasting on trees with survey COLT 2021 Structure-Aware Random Fourier Kernel for Graphs NeurIPS 2021 Structured World Belief for Reinforcement Learning in POMDP ICML 2021 Structure Learning of Undirected Graphical Models for Count Data JMLR 2021 Submodel Decomposition Bounds for Influence Diagrams AAAI 2021 Symbol Grounding and Task Learning from Imperfect Corrections ACL 2021 Testing Probabilistic Circuits NeurIPS 2021 The Base Measure Problem and its Solution AISTATS 2021 The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood COLT 2021 The Complexity of Bayesian Network Learning: Revisiting the Superstructure NeurIPS 2021 The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective NeurIPS 2021 The Minecraft Kernel: Modelling correlated Gaussian Processes in the Fourier domain AISTATS 2021 The neural moving average model for scalable variational inference of state space models UAI 2021 Thompson Sampling Algorithms for Cascading Bandits JMLR 2021