Bayesian Inference

Understanding the Variance Collapse of SVGD in High Dimensions ICLR 2022 Unifying Likelihood-free Inference with Black-box Optimization and Beyond ICLR 2022 Using Mixed-Effects Models to Learn Bayesian Networks from Related Data Sets PGM 2022 Variational inference via Wasserstein gradient flows NeurIPS 2022 Variational message passing neural network for Maximum-A-Posteriori (MAP) inference UAI 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 You Only Derive Once (YODO): Automatic Differentiation for Efficient Sensitivity Analysis in Bayesian Networks PGM 2022 K^2-GNN: Multiple Users’ Comments Integration with Probabilistic K-Hop Knowledge Graph Neural Networks ACML 2021 Active Bayesian Assessment of Black-Box Classifiers AAAI 2021 Active Learning for Bayesian 3D Hand Pose Estimation WACV 2021 AGENT: A Benchmark for Core Psychological Reasoning ICML 2021 A sampling-based circuit for optimal decision making NeurIPS 2021 Asymptotically Exact and Fast Gaussian Copula Models for Imputation of Mixed Data Types ACML 2021 Asynchronous $ε$-Greedy Bayesian Optimisation UAI 2021 Bayesian Argumentation-Scheme Networks: A Probabilistic Model of Argument Validity Facilitated by Argumentation Schemes EMNLP 2021 Bayesian Bellman Operators NeurIPS 2021 Bayesian Distributional Policy Gradients AAAI 2021 Bayesian Experience Reuse for Learning from Multiple Demonstrators IJCAI 2021 Bayesian Latent Factor Model for Higher-order Data ACML 2021 Bayesian Quadrature on Riemannian Data Manifolds ICML 2021 Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example AAAI 2021 Bias and variance of the Bayesian-mean decoder NeurIPS 2021 Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Word Embeddings and the Implications to Representation Learning AAAI 2021 Collapsed Variational Bounds for Bayesian Neural Networks NeurIPS 2021