Bayesian Inference

Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks UAI 2020 Generalizing Hand Segmentation in Egocentric Videos With Uncertainty-Guided Model Adaptation CVPR 2020 General Purpose MRF Learning with Neural Network Potentials IJCAI 2020 Generating Diverse Translation from Model Distribution with Dropout EMNLP 2020 Generative Semantic Hashing Enhanced via Boltzmann Machines ACL 2020 GP-NAS: Gaussian Process Based Neural Architecture Search CVPR 2020 GP-VAE: Deep Probabilistic Time Series Imputation AISTATS 2020 Gradient-Based Optimization for Bayesian Preference Elicitation AAAI 2020 Gradient-EM Bayesian Meta-Learning NeurIPS 2020 Graphical continuous Lyapunov models UAI 2020 Greedy inference with structure-exploiting lazy maps NeurIPS 2020 Hamiltonian Monte Carlo Swindles AISTATS 2020 Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond NeurIPS 2020 Handling the Positive-Definite Constraint in the Bayesian Learning Rule ICML 2020 HARK: Harshness-Aware Sentiment Analysis Framework for Product Review (Student Abstract) AAAI 2020 Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights NeurIPS 2020 Hierarchical Reinforcement Learning for Pedagogical Policy Induction (Extended Abstract) IJCAI 2020 High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds NeurIPS 2020 High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization NeurIPS 2020 Hypermodels for Exploration ICLR 2020 Hyperparameter Ensembles for Robustness and Uncertainty Quantification NeurIPS 2020 ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA NeurIPS 2020 Identifiability and Consistency of Bayesian Network Structure Learning from Incomplete Data PGM 2020 Implicit Generative Modeling for Efficient Exploration ICML 2020 Improved PAC-Bayesian Bounds for Linear Regression AAAI 2020