Bayesian & Probabilistic

Identification of Partially Observed Linear Causal Models: Graphical Conditions for the Non-Gaussian and Heterogeneous Cases NeurIPS 2021 Implicit Generative Copulas NeurIPS 2021 Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions NeurIPS 2021 Improving Causal Discovery By Optimal Bayesian Network Learning AAAI 2021 Improving Gaussian mixture latent variable model convergence with Optimal Transport ACML 2021 Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding ICML 2021 Improving Privacy Guarantee and Efficiency of Latent Dirichlet Allocation Model Training Under Differential Privacy EMNLP 2021 Inference of Black Hole Fluid-Dynamics From Sparse Interferometric Measurements ICCV 2021 Infinite Gaussian Mixture Modeling with an Improved Estimation of the Number of Clusters AAAI 2021 Information Directed Sampling for Sparse Linear Bandits NeurIPS 2021 Instance-Dependent Partial Label Learning NeurIPS 2021 Instance-Optimal Compressed Sensing via Posterior Sampling ICML 2021 Integrated Principal Components Analysis JMLR 2021 Interacting Knowledge Sources, Inspection and Analysis: Case-studies on Biomedical text processing EMNLP 2021 Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models NeurIPS 2021 Isometric Gaussian Process Latent Variable Model for Dissimilarity Data ICML 2021 It’s quality and quantity: the effect of the amount of comments on online suicidal posts EMNLP 2021 iVPF: Numerical Invertible Volume Preserving Flow for Efficient Lossless Compression CVPR 2021 Joint Demosaicking and Denoising in the Wild: The Case of Training Under Ground Truth Uncertainty AAAI 2021 Juice: A Julia Package for Logic and Probabilistic Circuits AAAI 2021 Kernel Continual Learning ICML 2021 Kernel Stein Discrepancy Descent ICML 2021 Kernel Thinning COLT 2021 Knowledge-Adaptation Priors NeurIPS 2021 Large-Scale Wasserstein Gradient Flows NeurIPS 2021