Bayesian & Probabilistic

The Star Geometry of Critic-Based Regularizer Learning NeurIPS 2024 The Virtual Driving Instructor: Multi-Agent System Collaborating via Knowledge Graph for Scalable Driver Education AAAI 2024 Think Global, Adapt Local: Learning Locally Adaptive K-Nearest Neighbor Kernel Density Estimators AISTATS 2024 This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization NeurIPS 2024 Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox NeurIPS 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 Generalizable and Interpretable Motion Prediction: A Deep Variational Bayes Approach 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 Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy ICLR 2024 Training Binary Neural Networks via Gaussian Variational Inference and Low-Rank Semidefinite Programming NeurIPS 2024 Transfer learning for tensor Gaussian graphical models JMLR 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 Trigonometric Quadrature Fourier Features for Scalable Gaussian Process Regression AISTATS 2024 Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions NeurIPS 2024 Uncertainty Estimation with Recursive Feature Machines UAI 2024 Uncertainty Quantification in Heterogeneous Treatment Effect Estimation with Gaussian-Process-Based Partially Linear Model AAAI 2024 Uncertainty Regularized Evidential Regression AAAI 2024 Uncertainty Resolution in Misinformation Detection EACL 2024 Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling UAI 2024 Unscrambling disease progression at scale: fast inference of event permutations with optimal transport NeurIPS 2024