Bayesian & Probabilistic

Addressing NER Annotation Noises with Uncertainty-Guided Tree-Structured CRFs EMNLP 2023 Adversarial Bayesian Augmentation for Single-Source Domain Generalization ICCV 2023 Adversarial Counterfactual Visual Explanations CVPR 2023 Adversarial robustness of amortized Bayesian inference ICML 2023 A Finite-Particle Convergence Rate for Stein Variational Gradient Descent NeurIPS 2023 A Geometric Deep Learning Framework for Generation of Virtual Left Ventricles as Graphs MIDL 2023 A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining ICML 2023 A Heavy-Tailed Algebra for Probabilistic Programming NeurIPS 2023 A Kernelized Stein Discrepancy for Biological Sequences ICML 2023 Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler COLT 2023 Aligning Language Models with Human Preferences via a Bayesian Approach NeurIPS 2023 Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification MIDL 2023 An Annotated Graph Model with Differential Degree Heterogeneity for Directed Networks JMLR 2023 An Eigenmodel for Dynamic Multilayer Networks JMLR 2023 An Empirical Bayes Framework for Open-Domain Dialogue Generation EMNLP 2023 A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference NeurIPS 2023 An Ordinal Latent Variable Model of Conflict Intensity ACL 2023 A normative theory of social conflict NeurIPS 2023 Any-scale Balanced Samplers for Discrete Space ICLR 2023 Approximate Bayesian Inference with Stein Functional Variational Gradient Descent ICLR 2023 Approximate Inference in Logical Credal Networks IJCAI 2023 Approximate inference of marginals using the IBIA framework NeurIPS 2023 Approximate Thompson Sampling via Epistemic Neural Networks UAI 2023 A Probabilistic Attention Model With Occlusion-Aware Texture Regression for 3D Hand Reconstruction From a Single RGB Image CVPR 2023 A Probabilistic Framework for Discovering New Intents ACL 2023