posterior distribution

DeePMOS: Deep Posterior Mean-Opinion-Score of Speech Interspeech 2023 Divide-and-Conquer Fusion JMLR 2023 Estimating the Contamination Factor’s Distribution in Unsupervised Anomaly Detection ICML 2023 Event Temporal Relation Extraction with Bayesian Translational Model EACL 2023 Exploration via Epistemic Value Estimation AAAI 2023 Federated Learning with Uncertainty via Distilled Predictive Distributions ACML 2023 Flat Seeking Bayesian Neural Networks NeurIPS 2023 GFlowOut: Dropout with Generative Flow Networks ICML 2023 Inferring Private Valuations from Behavioral Data in Bilateral Sequential Bargaining IJCAI 2023 Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network NeurIPS 2023 Leveraging Future Relationship Reasoning for Vehicle Trajectory Prediction ICLR 2023 Mini-batching error and adaptive Langevin dynamics JMLR 2023 On permutation symmetries in Bayesian neural network posteriors: a variational perspective NeurIPS 2023 Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguous Inputs ICML 2023 Quantification of Uncertainty with Adversarial Models NeurIPS 2023 Reinforcement Causal Structure Learning on Order Graph AAAI 2023 StackFLOW: Monocular Human-Object Reconstruction by Stacked Normalizing Flow with Offset IJCAI 2023 Stein Π-Importance Sampling NeurIPS 2023 Taking the neural sampling code very seriously: A data-driven approach for evaluating generative models of the visual system NeurIPS 2023 Target-Side Augmentation for Document-Level Machine Translation ACL 2023 The Lie-Group Bayesian Learning Rule AISTATS 2023 Thompson Sampling with Less Exploration is Fast and Optimal ICML 2023 Tree Variational Autoencoders NeurIPS 2023 Uncertainty Quantification via Neural Posterior Principal Components NeurIPS 2023 VaRT: Variational Regression Trees NeurIPS 2023