Bayesian & Probabilistic

Sparse Additive Gaussian Process Regression JMLR 2022 Sparse Continuous Distributions and Fenchel-Young Losses JMLR 2022 Sparse Gaussian Process Hyperparameters: Optimize or Integrate? NeurIPS 2022 Sparse Probabilistic Circuits via Pruning and Growing NeurIPS 2022 Speeding up approximate MAP by applying domain knowledge about relevant variables PGM 2022 Split Hierarchical Variational Compression CVPR 2022 Sqrt(d) Dimension Dependence of Langevin Monte Carlo ICLR 2022 Stochastic Multiple Target Sampling Gradient Descent NeurIPS 2022 Structural Kernel Search via Bayesian Optimization and Symbolical Optimal Transport NeurIPS 2022 Structure learning algorithms for multidimensional continuous-time Bayesian network classifiers PGM 2022 Surrogate Likelihoods for Variational Annealed Importance Sampling ICML 2022 Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data NeurIPS 2022 Tagging Without Rewriting: A Probabilistic Model for Unpaired Sentiment and Style Transfer ACL 2022 Temporal Knowledge Graph Completion with Approximated Gaussian Process Embedding COLING 2022 The AIM and EM Algorithms for Learning from Coarse Data JMLR 2022 The Dual PC Algorithm for Structure Learning PGM 2022 The Neural Testbed: Evaluating Joint Predictions NeurIPS 2022 The query complexity of sampling from strongly log-concave distributions in one dimension COLT 2022 The Role of Context and Uncertainty in Shallow Discourse Parsing COLING 2022 Thinned random measures for sparse graphs with overlapping communities NeurIPS 2022 Top Two Algorithms Revisited NeurIPS 2022 Toward Annotator Group Bias in Crowdsourcing ACL 2022 Towards a Theory of Non-Log-Concave Sampling:First-Order Stationarity Guarantees for Langevin Monte Carlo COLT 2022 Towards Federated Bayesian Network Structure Learning with Continuous Optimization AISTATS 2022 Towards Improved Zero-shot Voice Conversion with Conditional DSVAE Interspeech 2022