Probabilistic Modeling

Local Justice and Machine Learning: Modeling and Inferring Dynamic Ethical Preferences toward Allocations AAAI 2023 Log-FGAER: Logic-Guided Fine-Grained Address Entity Recognition from Multi-Turn Spoken Dialogue EMNLP 2023 Multi-Relational Probabilistic Event Representation Learning via Projected Gaussian Embedding ACL 2023 Multi Time Scale World Models NeurIPS 2023 Multivariate Probabilistic Monocular 3D Object Detection WACV 2023 Nearest Neighbor Dirichlet Mixtures JMLR 2023 NeuPSL: Neural Probabilistic Soft Logic IJCAI 2023 Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series ICML 2023 Neural Spline Search for Quantile Probabilistic Modeling AAAI 2023 Nonlinear Structural Equation Model Guided Gaussian Mixture Hierarchical Topic Modeling ACL 2023 Normalizing Flow Ensembles for Rich Aleatoric and Epistemic Uncertainty Modeling AAAI 2023 Normalizing Flows for Interventional Density Estimation ICML 2023 Novel Ordering-Based Approaches for Causal Structure Learning in the Presence of Unobserved Variables AAAI 2023 On a Class of Gibbs Sampling over Networks COLT 2023 On Calibrating Diffusion Probabilistic Models NeurIPS 2023 On Distance and Kernel Measures of Conditional Dependence JMLR 2023 One-Shot Compression of Large Edge-Exchangeable Graphs using Bits-Back Coding ICML 2023 On the Calibration of Probabilistic Classifier Sets AISTATS 2023 On the Estimation of Gaussian Mixture Copula Models ICML 2023 On the Identifiability and Estimation of Causal Location-Scale Noise Models ICML 2023 On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study EMNLP 2023 Personalized Federated Learning under Mixture of Distributions ICML 2023 Pitfalls of Gaussians as a noise distribution in NCE ICLR 2023 Probabilistic Conformal Prediction Using Conditional Random Samples AISTATS 2023 Probabilistic Querying of Continuous-Time Event Sequences AISTATS 2023