Bayesian Inference

Estimating Epistemic and Aleatoric Uncertainty with a Single Model NeurIPS 2024 Estimating the Hallucination Rate of Generative AI NeurIPS 2024 Evaluating Large Language Models along Dimensions of Language Variation: A Systematik Invesdigatiom uv Cross-lingual Generalization EMNLP 2024 Event-triggered safe Bayesian optimization on quadcopters L4DC 2024 Evidence Estimation in Gaussian Graphical Models Using a Telescoping Block Decomposition of the Precision Matrix JMLR 2024 Evidential Uncertainty-Guided Mitochondria Segmentation for 3D EM Images AAAI 2024 Exact Inference for Continuous-Time Gaussian Process Dynamics AAAI 2024 Expected Probabilistic Hierarchies NeurIPS 2024 Explaining Language Model Predictions with High-Impact Concepts EACL 2024 Exploiting Human-AI Dependence for Learning to Defer ICML 2024 Exploring Active Learning in Meta-Learning: Enhancing Context Set Labeling ECCV 2024 Fast Fourier Bayesian Quadrature AISTATS 2024 Fast Value Tracking for Deep Reinforcement Learning ICLR 2024 Fearless Stochasticity in Expectation Propagation NeurIPS 2024 Federated Label-Noise Learning with Local Diversity Product Regularization AAAI 2024 FedFisher: Leveraging Fisher Information for One-Shot Federated Learning AISTATS 2024 FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation NeurIPS 2024 FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning ICLR 2024 Feel-Good Thompson Sampling for Contextual Dueling Bandits ICML 2024 Few-shot Temporal Pruning Accelerates Diffusion Models for Text Generation COLING 2024 Fine-Tuning Language Models with Differential Privacy through Adaptive Noise Allocation EMNLP 2024 Fixed Confidence Best Arm Identification in the Bayesian Setting NeurIPS 2024 Fixing Overconfidence in Dynamic Neural Networks WACV 2024 Flexible Bayesian Product Mixture Models for Vector Autoregressions JMLR 2024 FlexiBO: A Decoupled Cost-Aware Multi-objective Optimization Approach for Deep Neural Networks (Abstract Reprint) AAAI 2024