bayesian inference

Tuning-Free Generalized Hamiltonian Monte Carlo AISTATS 2022 Uncertainty Modeling for Out-of-Distribution Generalization ICLR 2022 Uncertainty Modeling in Generative Compressed Sensing ICML 2022 Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective NeurIPS 2022 VaiPhy: a Variational Inference Based Algorithm for Phylogeny NeurIPS 2022 Variational inference via Wasserstein gradient flows NeurIPS 2022 Variational methods for simulation-based inference ICLR 2022 Variational multiple shooting for Bayesian ODEs with Gaussian processes UAI 2022 Variational oracle guiding for reinforcement learning ICLR 2022 K^2-GNN: Multiple Users’ Comments Integration with Probabilistic K-Hop Knowledge Graph Neural Networks ACML 2021 A Bayesian Approach for Subset Selection in Contextual Bandits AAAI 2021 A Bayesian Contiguous Partitioning Method for Learning Clustered Latent Variables JMLR 2021 A Bayesian Framework for Information-Theoretic Probing EMNLP 2021 A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics NeurIPS 2021 Active Bayesian Assessment of Black-Box Classifiers AAAI 2021 Active Latent Space Shape Model: A Bayesian Treatment of Shape Model Adaptation With an Application to Psoriatic Arthritis Radiographs WACV 2021 Active Learning for Bayesian 3D Hand Pose Estimation WACV 2021 Active Learning for Sequence Tagging with Deep Pre-trained Models and Bayesian Uncertainty Estimates EACL 2021 Adaptive Knowledge Driven Regularization for Deep Neural Networks AAAI 2021 A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning NeurIPS 2021 A General Class of Transfer Learning Regression without Implementation Cost AAAI 2021 A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction ICCV 2021 A Hybrid Approximation to the Marginal Likelihood AISTATS 2021 A Hybrid Stochastic Gradient Hamiltonian Monte Carlo Method AAAI 2021 A Language for Counterfactual Generative Models ICML 2021