Probabilistic Modeling

Sparse Continuous Distributions and Fenchel-Young Losses JMLR 2022 Sparse Probabilistic Circuits via Pruning and Growing NeurIPS 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 Neural Testbed: Evaluating Joint Predictions NeurIPS 2022 The Role of Context and Uncertainty in Shallow Discourse Parsing COLING 2022 Thinned random measures for sparse graphs with overlapping communities NeurIPS 2022 Toward Annotator Group Bias in Crowdsourcing ACL 2022 Trusted Multi-View Deep Learning with Opinion Aggregation AAAI 2022 Truth-Tracking via Approval Voting: Size Matters AAAI 2022 Two-way Sparse Network Inference for Count Data AISTATS 2022 Uncertainty-Guided Probabilistic Transformer for Complex Action Recognition CVPR 2022 Uniform deconvolution for Poisson Point Processes JMLR 2022 VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming NeurIPS 2022 Variational Inference with Locally Enhanced Bounds for Hierarchical Models ICML 2022 Weak Separation in Mixture Models and Implications for Principal Stratification AISTATS 2022 Who did it? Identifying the Most Likely Origins of Events PGM 2022 Why the Rich Get Richer? On the Balancedness of Random Partition Models ICML 2022 Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling ICML 2022 You Are What You Talk About: Inducing Evaluative Topics for Personality Analysis EMNLP 2022 A Bayesian Contiguous Partitioning Method for Learning Clustered Latent Variables JMLR 2021 A Bayesian Framework for Information-Theoretic Probing EMNLP 2021 A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference NeurIPS 2021