Probabilistic Modeling

Surrogate Bayesian Networks for Approximating Evolutionary Games AISTATS 2024 Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning NeurIPS 2024 Tensor-train methods for sequential state and parameter learning in state-space models JMLR 2024 The ALℓ_0CORE Tensor Decomposition for Sparse Count Data AISTATS 2024 Theory-guided Message Passing Neural Network for Probabilistic Inference AISTATS 2024 Toward Conditional Distribution Calibration in Survival Prediction NeurIPS 2024 Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning NeurIPS 2024 Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts AISTATS 2024 Towards Modeling Uncertainties of Self-Explaining Neural Networks via Conformal Prediction AAAI 2024 Towards Multi-Mode Outlier Robust Tensor Ring Decomposition AAAI 2024 Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting ICLR 2024 Transition Constrained Bayesian Optimization via Markov Decision Processes NeurIPS 2024 TreeVI: Reparameterizable Tree-structured Variational Inference for Instance-level Correlation Capturing NeurIPS 2024 Uncertainty Regularized Evidential Regression AAAI 2024 Uncertainty Resolution in Misinformation Detection EACL 2024 Unscrambling disease progression at scale: fast inference of event permutations with optimal transport NeurIPS 2024 Using Autodiff to Estimate Posterior Moments, Marginals and Samples UAI 2024 Value-Based Abstraction Functions for Abstraction Sampling UAI 2024 Virtual-Event-Based Posterior Sampling and Inference for Neyman-Scott Processes JMLR 2024 What does guidance do? A fine-grained analysis in a simple setting NeurIPS 2024 Zero Inflation as a Missing Data Problem: a Proxy-based Approach UAI 2024 Adaptive Riemannian stochastic gradient descent and reparameterization for Gaussian mixture model fitting ACML 2023 An Annotated Graph Model with Differential Degree Heterogeneity for Directed Networks JMLR 2023 A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference NeurIPS 2023 An Ordinal Latent Variable Model of Conflict Intensity ACL 2023