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Bayesian Inference

4821 directly classified papers

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Papers

Infinite-dimensional Mahalanobis Distance with Applications to Kernelized Novelty Detection JMLR 2025
Kernel Learning for Sample Constrained Black-Box Optimization AAAI 2025
INDRA: Iterative Difficulty Refinement Attention for MCQ Difficulty Estimation for Indic Languages IJCNLP 2025
Bayes Meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes JMLR 2025
Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization JMLR 2025
Selective Inference with Distributed Data JMLR 2025
Bayesian Multi-Group Gaussian Process Models for Heterogeneous Group-Structured Data JMLR 2025
Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding JMLR 2025
Determine the Number of States in Hidden Markov Models via Marginal Likelihood JMLR 2025
Fine-Grained Change Point Detection for Topic Modeling with Pitman-Yor Process JMLR 2025
Sampling and Estimation on Manifolds using the Langevin Diffusion JMLR 2025
On Consistent Bayesian Inference from Synthetic Data JMLR 2025
Beyond Completion: A Foundation Model for General Knowledge Graph Reasoning ACL 2025
One-for-All Pruning: A Universal Model for Customized Compression of Large Language Models ACL 2025
Generalization-Preserved Learning: Closing the Backdoor to Catastrophic Forgetting in Continual Deepfake Detection ICCV 2025
Uncertainty-Aware Iterative Preference Optimization for Enhanced LLM Reasoning ACL 2025
Agreement-Constrained Probabilistic Minimum Bayes Risk Decoding AACL 2025
Data-scarce Behavior Editing of Language Models EMNLP 2025
Benchmarking Uncertainty Metrics for LLM Target-Aware Search EMNLP 2025
Questioning Our Questions: How Well Do Medical QA Benchmarks Evaluate Clinical Capabilities of Language Models? ACL 2025
SafeConf: A Confidence-Calibrated Safety Self-Evaluation Method for Large Language Models EMNLP 2025
Confidence-Aware Reasoning: Optimizing Self-Guided Thinking Trajectories in Large Reasoning Models EMNLP 2025
pEBR: A Probabilistic Approach to Embedding Based Retrieval EMNLP 2025
Explain then Rank: Scale Calibration of Neural Rankers Using Natural Language Explanations from LLMs ACL 2025
KGE Calibrator: An Efficient Probability Calibration Method of Knowledge Graph Embedding Models for Trustworthy Link Prediction EMNLP 2025