Bayesian Inference

Dynamic Knowledge Injection for AIXI Agents AAAI 2024 Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior ICML 2024 Efficient Detection of LLM-generated Texts with a Bayesian Surrogate Model ACL 2024 Efficient Exploration for LLMs ICML 2024 Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling ICML 2024 Efficient Hyperparameter Optimization with Adaptive Fidelity Identification CVPR 2024 Efficient LLM Comparative Assessment: A Product of Experts Framework for Pairwise Comparisons EMNLP 2024 Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning AISTATS 2024 Efficient Mixture Learning in Black-Box Variational Inference ICML 2024 Efficient Nonparametric Tensor Decomposition for Binary and Count Data AAAI 2024 Efficient Variational Sequential Information Control AISTATS 2024 EigenVI: score-based variational inference with orthogonal function expansions NeurIPS 2024 Embarrassingly Parallel GFlowNets ICML 2024 EMC$^2$: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence ICML 2024 Empowering Active Learning for 3D Molecular Graphs with Geometric Graph Isomorphism NeurIPS 2024 Enabling Mixed Effects Neural Networks for Diverse, Clustered Data Using Monte Carlo Methods IJCAI 2024 Energy-based Automated Model Evaluation ICLR 2024 Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations ICLR 2024 Energy-based Epistemic Uncertainty for Graph Neural Networks NeurIPS 2024 Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling ICLR 2024 Entropy-MCMC: Sampling from Flat Basins with Ease ICLR 2024 Epistemic Uncertainty Quantification For Pre-Trained Neural Networks CVPR 2024 Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels AISTATS 2024 Error bounds for any regression model using Gaussian processes with gradient information AISTATS 2024 Estimating before Debiasing: A Bayesian Approach to Detaching Prior Bias in Federated Semi-Supervised Learning IJCAI 2024