Bayesian & Probabilistic

Error-Correcting and Verifiable Parallel Inference in Graphical Models AAAI 2020 Estimation and Imputation in Probabilistic Principal Component Analysis with Missing Not At Random Data NeurIPS 2020 Event-Driven Continuous Time Bayesian Networks AAAI 2020 Experimental Design for Optimization of Orthogonal Projection Pursuit Models AAAI 2020 Exploiting Higher Order Smoothness in Derivative-free Optimization and Continuous Bandits NeurIPS 2020 Exponential Family Graph Embeddings AAAI 2020 Factor Graph Grammars NeurIPS 2020 Fairness constraints can help exact inference in structured prediction NeurIPS 2020 Fast and Flexible Temporal Point Processes with Triangular Maps NeurIPS 2020 Fast Bayesian Inference of Sparse Networks with Automatic Sparsity Determination JMLR 2020 Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev NeurIPS 2020 Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC NeurIPS 2020 f-Divergence Variational Inference NeurIPS 2020 Federated Bayesian Optimization via Thompson Sampling NeurIPS 2020 Federated Latent Dirichlet Allocation: A Local Differential Privacy Based Framework AAAI 2020 Flexible Prior Elicitation via the Prior Predictive Distribution UAI 2020 Flow Contrastive Estimation of Energy-Based Models CVPR 2020 Fragmentation Coagulation Based Mixed Membership Stochastic Blockmodel AAAI 2020 Free Energy Wells and Overlap Gap Property in Sparse PCA COLT 2020 From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models ICML 2020 From Support Propagation to Belief Propagation in Constraint Programming (Extended Abstract) IJCAI 2020 GaSPing for Utility AAAI 2020 Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective NeurIPS 2020 Gaussian Sum-Product Networks Learning in the Presence of Interval Censored Data PGM 2020 GenDICE: Generalized Offline Estimation of Stationary Values ICLR 2020