Bayesian & Probabilistic

A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors ICLR 2024 A Tractable Inference Perspective of Offline RL NeurIPS 2024 A Unified View of FANOVA: A Comprehensive Bayesian Framework for Component Selection and Estimation ICML 2024 A Unifying Normative Framework of Decision Confidence NeurIPS 2024 Automated Statistical Model Discovery with Language Models ICML 2024 A Variational Approach to Bayesian Phylogenetic Inference JMLR 2024 A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error ICLR 2024 Backward Filtering Forward Deciding in Linear Non-Gaussian State Space Models AISTATS 2024 Balancing Computational Cost and Accuracy in Inference of Continuous Bayesian Networks PGM 2024 Bayesian Active Learning in the Presence of Nuisance Parameters UAI 2024 Bayesian Adaptation of Network Depth and Width for Continual Learning ICML 2024 Bayesian Adaptive Calibration and Optimal Design NeurIPS 2024 Bayesian Calibration of Win Rate Estimation with LLM Evaluators EMNLP 2024 Bayesian Coreset Optimization for Personalized Federated Learning ICLR 2024 Bayesian Design Principles for Offline-to-Online Reinforcement Learning ICML 2024 Bayesian Differentiable Physics for Cloth Digitalization CVPR 2024 Bayesian Diffusion Models for 3D Shape Reconstruction CVPR 2024 Bayesian Example Selection Improves In-Context Learning for Speech, Text and Visual Modalities EMNLP 2024 Bayesian Exploration Networks ICML 2024 Bayesian-guided Label Mapping for Visual Reprogramming NeurIPS 2024 Bayesian Inference with Complex Knowledge Graph Evidence AAAI 2024 Bayesian Low-rank Adaptation for Large Language Models ICLR 2024 Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation ICLR 2024 Bayesian Online Natural Gradient (BONG) NeurIPS 2024 Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal NeurIPS 2024